WO2019120195A1

WO2019120195A1 - Indoor navigation system using inertial sensors and short-wavelength low energy device

Info

Publication number: WO2019120195A1
Application number: PCT/CN2018/121793
Authority: WO
Inventors: Kin Siu NG
Original assignee: Fruit Innovations Ltd
Current assignee: Fruit Innovations Ltd
Priority date: 2017-12-18
Filing date: 2018-12-18
Publication date: 2019-06-27
Anticipated expiration: 2020-06-18
Also published as: CN111684236A

Abstract

A system for a tracking device and and a method thereof is provided, the system comprises: a wireless module for receiving location reference from an external wireless device, and determining distances from the external wireless devices; an inertial measurement unit (IMU) having an accelerometer for obtaining an acceleration vector and a gyroscope for obtaining an angular velocity vector; a processing unit for determining a first estimated coordinate relative to a global frame from the location reference, calculating a second estimate coordinate relative to the global frame with the acceleration vector, the angular velocity vector, and the ambient atmospheric pressure.

Description

Indoor Navigation System using inertial sensors and Short-Wavelength Low Energy Device

TECHNICAL FIELD

The invention relates to an indoor navigation system, and in particular, although not exclusively, to an indoor navigation system using inertial sensors and Bluetooth beacon.

BACKGROUND

Electronic navigation systems were developed around the 1940s. Scientists were able to track the Sputnik satellite with the Doppler effect of the shifts in its radio signal. The signals transmitted by the satellites can be used by a land receiver for navigation. Such systems were typically known as the Global Positioning System (GPS) .

In order to effectively operate a navigation system using the GPS satellite signals, the GPS receiver must be able to access the signs from at least four satellites. Although it is possible to calculate an estimated position of the GPS receiver with the signs from three satellites, that position was calculated with the assumption that the GPS receiver was located at mean sea level. If the GPS receiver is at mean sea level, the position will be reasonably accurate. However if the GPS receiver is substantially above or below mean sea level, the calculated position would not be even close to the real position.

In an open area, such as flying in air space or sailing in the open sea, it would usually be relatively easy to gain access to four satellites at the same time.

However, since the GPS satellite signals with frequency radio wave signals (1575.42 MHZ and 1227.6 MHZ) are designed to travel long distance but have low penetration. When the GPS receiver antenna is inside a city surrounded by tall structures or inside a building, there is no direct line-of-sight reception of multiple satellites signals. It is impossible for the GPS receiver to accurately calculate the current location.

Traditional systems for navigating within a building are generally costly or ineffective. For example, the installation and operating costs associated with an installed base of radio frequency markers within a building are substantial barriers not readily overcome. In addition, poor reception of radio frequency navigation signals within a building, such as that used by satellite-based navigation systems (for example, global positioning systems) , precludes widespread acceptance.

SUMMARY OF THE INVENTION

The present invention may overcome or ameliorate at least one of the disadvantages of the prior art, or to provide a useful alternative.

Other advantages of the invention will become apparent when taken into consideration with the following specification and drawings.

In accordance with a first aspect of the present invention, there is provided a tracking device comprising: a wireless module for receiving location reference from an external wireless device, and determine distances from the external wireless devices; an inertial measurement unit (IMU) having an accelerometer for obtaining an acceleration vector and a gyroscope for obtaining an angular velocity vector; and a processing unit for determining a first estimated coordinate relative to a global frame from the location reference, calculating a second estimate coordinate relative to the global frame with the acceleration vector, the angular velocity vector, and the ambient atmospheric pressure.

In an embodiment of the first aspect, the IMU further comprises a magnetometer for measuring a magnetic field vector of an external magnetic field and/or a pressure sensor for obtaining an ambient atmospheric pressure.

In an embodiment of the first aspect, the IMU is adapted to carry out self-calibration for the accelerometer and gyroscope.

In an embodiment of the first aspect, the IMU comprises a step counter for counting a number indicating of steps moved thereof.

In an embodiment of the first aspect, the IMU is adapted to derive a stride length by integrating the acceleration vector and the number of steps.

In an embodiment of the first aspect, the processing unit is adapted to derive an estimate attitude relative to the global frame with the angular velocity vector obtain from the IMU.

In an embodiment of the first aspect, the processing unit is adapted to derive an estimate displacement vector relative to the global frame with the angular velocity vector obtain from the IMU and the acceleration vector from the IMU.

In an embodiment of the first aspect, the processing unit is adapted to derive the second estimate coordinate with the displacement vector and the first estimate coordinate.

In an embodiment of the first aspect, the processing unit is adapted to forward the second estimate coordinate to a computer processor, wherein the computer processor is adapted to generate a relative current position on a local map.

In an embodiment of the first aspect, the computer processor is associated with a display screen to display the local map and the relative current position and the local map on the display screen.

In an embodiment of the first aspect, the computer processer is adapted to generate navigation information to display on the display screen.

In an embodiment of the first aspect, the computer processor is associated with a speech module to play the navigation information in an audible format on a speaker.

In an embodiment of the first aspect, the computer processor is configured on a smart device.

In an embodiment of the first aspect, the smart device is any one of the smart phone, handheld tablet, laptop computer, desktop computer, Electronic Positioning System, vehicles, aircraft, drone, robot, vessel, and biomechanical device.

In an embodiment of the first aspect, the tracking device further comprises a hardware interface to electrically connected to the computer processor.

In an embodiment of the first aspect, the tracking device further comprises means for installing on a wearable device.

In an embodiment of the first aspect, the wireless module is adapted to communicate with a wireless communication module electrically connected to the computer processor.

In an embodiment of the first aspect, the wireless module is adapted to communicate with the wireless device through a wireless protocol.

In an embodiment of the first aspect, the wireless protocol is any one of Bluetooth protocol, Wi-Fi protocol, and Li-Fi protocol.

In an embodiment of the first aspect, the location reference is embedded in a data packet comprising a universal unique identifier (UUDI) of the wireless device and a data payload.

In an embodiment of the first aspect, the data packet is broadcast by the wireless device at a predetermined time cycle.

In an embodiment of the first aspect, the wireless device is configured to broadcast a plurality of data packet in one predetermined time cycle, wherein each data packet comprises the UUDI of the wireless device and a different location reference in the payload.

In an embodiment of the first aspect, the data payload is encrypted.

In an embodiment of the first aspect, the wireless device is adapted to communicate with a server through a secured channel, such that the server is adapted to configure the wireless device remotely.

In an embodiment of the first aspect, the processing unit is adapted to forward the location reference to the computer processor, wherein the computer processor is adapted to retrieve a global coordinate from a location database with the location reference.

In an embodiment of the first aspect, the location database is installed on a server.

In an embodiment of the first aspect, the computer processor is associated with a network module to communicate with the server through a network.

In an embodiment of the first aspect, the wireless module is further arranged to determine distances from at least one beacon device.

In an embodiment of the first aspect, the beacon device includes a Bluetooth beacon.

In an embodiment of the first aspect, the beacon device is arranged radiate uni-directionally.

In an embodiment of the first aspect, the beacon device comprises a uni-directional antenna.

In accordance to a second aspect of the present invention, there is provided an indoor navigation method using a tracking device, and one or more wireless device, comprising the steps of: receiving location reference from the one or more wireless devices, and determine distances from the devices; determining a first estimated coordinate relative to a global frame from the location reference; obtaining an acceleration vector via an accelerometer of an inertial measurement unit (IMU) of the tracking device; obtaining an angular velocity vector via a gyroscope of the IMU; and calculating a second estimate coordinate relative to the global frame with the acceleration vector, the angular velocity vector, and the ambient atmospheric pressure.

In an embodiment of the second aspect, the method further comprises the step of: obtaining a magnetic field vector of an external magnetic field via a magnetometer for measuring on the IMU; and/or obtaining an ambient atmospheric pressure via a pressure sensor of the IMU.

In an embodiment of the second aspect, the method further comprises the step of performing self-calibration for the accelerometer and gyroscope.

In an embodiment of the second aspect, the method further comprises the step of obtaining a value indicating steps moved via a step counter of the IMU.

In an embodiment of the second aspect, the method further comprises the step of deriving a stride length by integrating the acceleration vector and the number of steps.

In an embodiment of the second aspect, the method further comprises the step of deriving an estimate attitude relative to the global frame with the angular velocity vector obtained from the IMU.

In an embodiment of the second aspect, the method further comprises the step of deriving an estimate displacement vector relative to the global frame with the angular velocity vector and the acceleration vector.

In an embodiment of the second aspect, the method further comprises the step of deriving the second estimate coordinate with the displacement vector and the first estimate coordinate.

In an embodiment of the second aspect, the method further comprises the step of forwarding the second estimate coordinate to a smart device, wherein the smart device is adapted to generate a relative current position on a local map.

In an embodiment of the second aspect, the smart device is associated with a display screen to display the local map and the relative current position and the local map on the display screen.

In an embodiment of the second aspect, the smart device is adapted to generate navigation information to display on the display screen.

In an embodiment of the second aspect, the smart device is associated with a speech module to play the navigation information in an audible format on a speaker.

It is therefore an advantage of the present invention to provide a navigation system in an enclosed environment, in particular, to provide an indoor navigation system.

Advantageously, the navigation system utilises inertial sensors and radio frequency signal to determine current location.

It is another advantage of the present invention to provide an indoor navigation system using both inertial sensors and radio frequency beacon to provide accurate navigation information to users.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the present invention will now be described, by way of example, with reference to the accompanying drawings in which:

Fig. 1 is a schematic diagram showing a system of an indoor navigation system in according to an embodiment of the present invention;

Fig. 2 is a schematic diagram of a hardware platform for the indoor navigation system of Fig. 1;

Fig. 3 is a schematic diagram of a process for calculating current position for the indoor navigation system of Fig. 1;

Fig. 4 is a schematic diagram of a strap down navigator algorithm of the indoor navigation system of Fig. 1;

Fig. 5 is a schematic diagram of an example of navigation process of the indoor navigation system of Fig. 1;

Fig. 6 is a schematic diagram of an example operation of two beacons radiating omni-directional signals;

Fig. 7 is a schematic diagram showing detection of the omni-directional beacon signal radiated from a single source at three different locations;

Fig. 8 is a schematic diagram showing an example operation of two beacons radiating uni-directional signals; and

Fig. 9 is is a schematic diagram showing detection of the uni-directional beacon signal radiated from a single source at three different locations.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

The inventors have, through their own research, trials and experiments, devised that portable devices may be used for tracking an object as well as providing real-time navigation information based on the tracked location.

In one example embodiment, a portable device that generated position and orientation data to facilitate movement within a building may be used. The device could be, for example, handheld or affixed to a cane. Data for navigation was derived from reflections from interior surfaces and dead reckoning sensors. The portable device comprised a first sensor configured to provide rotational velocity data; a second sensor configured to provide distance data based on a reflected signal; and a processor coupled to the first sensor and the second sensor and configured to execute an algorithm using the rotation velocity data and the distance data to determine at least one of a position relative to a landmark and a heading relative to the landmark. This prior art depends on the sensors of the device which could be inaccurate due to bias, noises, flickers, drifts, and other environmental disturbances.

In an alternatively example, there is provided a navigation device for guiding people around urban environments indoor and outdoor using existing cellular phone as mobile application displaying content and navigation. The mobile application comprised steps of: a) loading a local area/facility map; b) determining a current position with wireless radio frequency (RF) beacons; c) displaying said current position on the cellular phone; d) navigating between positions of beacons as shown on the local area/facility maps, e) receiving local content based upon a location of the display device as identified by beacon identifiers of proximate beacons.

In yet another example embodiment, a navigation system having a series of RF beacons deployed about a localized area to create an infrastructure may be used. The mobile application disclosed could utilize the RF beacons to determine a user's location respective to a local area and inform the user of their location on an associated map. The mobile application comprised steps of: scanning for any of local beacon signals using a mobile device; decoding the beacon signal to obtain said included known respective beacon physical location information, and determining a current location of said mobile device within said interior of an enclosed structure of said at least one enclosed structure, wherein said current location of said mobile device is determined based upon respective beacon physical location information decoded from said received beacon signal.

Embodiments of the present invention will now be described in detail with reference to the drawings, which are provided as illustrative examples of the invention so as to enable those skilled in the art to practice the invention. Notably, the figures and examples below are not meant to limit the scope of the present invention to a single embodiment, but other embodiments are possible by way of interchange of some or all of the described or illustrated elements. Moreover, where certain elements of the present invention can be partially or fully implemented using known components, only those portions of such known components that are necessary for an understanding of the present invention will be described, and detailed descriptions of other portions of such known components will be omitted so as not to obscure the invention. Embodiments described as being implemented in software should not be limited thereto, but can include embodiments implemented in hardware, or combinations of software and hardware, and vice-versa, as will be apparent to those skilled in the art, unless otherwise specified herein. In the present specification, an embodiment showing a singular component should not be considered limiting; rather, the invention is intended to encompass other embodiments including a plurality of the same component, and vice-versa, unless explicitly stated otherwise herein. Moreover, applicants do not intend for any term in the specification or claims to be ascribed an uncommon or special meaning unless explicitly set forth as such. Further, the present invention encompasses present and future known equivalents to the known components referred to herein by way of illustration.

The present invention relates to an invention relates to an indoor navigation system using inertial sensors and radio (RF) frequency beacons. In one embodiment of the present invention, there is provided a smart device combined with RF low-energy-beacon and inertial sensors multi-floor indoor navigation system.

In one embodiment as shown in Fig. 1, there is provided a an indoor navigation system 10 comprising a handheld device 12 having one or more inertial sensors for position calibration and detection, a memory unit for storing an indoor map; an RF processing unit for receiving and processing RF signal broadcast by one or more external RF beacons 14.

In one preferred embodiment of an indoor navigation system of the present invention, the system comprises: a RF enable wearable device, a smart device with specific built-in software application and indoor digital map; and one or more RF beacons. In a preferred embodiment, the RF beacon is a Bluetooth or Bluetooth low-energy (BLE) Beacon adapted to communicate through Bluetooth protocol. In another embodiment, the RF beacon is a Wi-Fi Beacon adapted to communicate through Wi-Fi protocol. In yet another embodiment, the RF Beacon is a Li-Fi Beacon adapted to communicate through Li-Fi protocol.

In one embodiment of the present invention as shown in Fig. 2, there is provide a tracking device 20 comprising: a low energy wireless module (BLE module) 26 for receiving location reference from one external low energy wireless device (BLE device) 14, and determine a distance from the external low energy device; a inertial measurement unit (IMU) 28 have an accelerometer for measuring the acceleration vector, and a gyroscope for measuring angular velocity vector, a processing unit 22 for determining an first estimated global coordinate from the location reference, calculating a second estimate global coordinate with the acceleration vector, the angular velocity vector, and the ambient atmospheric pressure.

Optionally, the IMU 28 may further comprise a magnetometer for measuring a magnetic field vector of an external magnetic field and/or a pressure sensor for obtaining an ambient atmospheric pressure. These additional detectors may provide supplementary information for the determination of the real-time position of the tracking device.

In one preferred embodiment, the processing unit 22 may be used for configuring one or more algorithms in determining one or more of the first estimate global coordinate and the second estimate global coordinate. In another embodiment the algorithms in determining one or more of the first estimate global coordinate and the second estimate global coordinate is preprogrammed and stored in the memory unit associate to the processing unit 22.

In a preferred embodiment, the smart device 12 can be any one of the smart phone, handheld tablet, laptop computer, desktop computer, Electronic Positioning System, vehicles, aircraft, drone, robot, vessel, and biomechanical device. In another, embodiment, the smart device can be a single board computer, or even a microprocessor.

In another preferred embodiment, the wearable device and the smart device comprises a positing circuit or microcontroller as shown in Fig. 2. The positioning circuit 20 has a processing core, such as a digital signal processor (DSP) , a field programmable gates array (FPGA) , a programmable logic device (PLD) , a programmable microcontroller, or a computer processor. Different components in the processing unit may be engineer to perform different tasks in the tracking process. For example, a DSP may be adapted to performing complex calculations and task scheduling, an FPGA or a PLD may be adapted to carrying out high-speed digital signal processing in parallel and interface control. The RF Unit 26 and the Inertial Measurement Unit (IMU) 28 are used to receive RF signals and inertial data, which are connected to the processor by the I/O of FPGA . The IMU 28 may comprise a tri-axis accelerometer, a tri-axis gyroscope, tri-axis magnetometer, and altimeter or barometric sensor. In addition, all units on the positioning circuit 20 may share the same clock, which can be temperature-compensated crystal oscillator (TCXO) , oven-controlled crystal oscillator (OCXO) or other external clocks.

Preferably, tri-axis accelerometer may be included inside the wearable device or smart device of the preferred embodiment is adapted to measuring acceleration, which is the rate of change of the velocity of an object. The measurement unit of an embodiment of the present invention is meter per squared second (m/s ²) or in G-forces (g) . Typically, the accelerometer is adapted to sensing either static or dynamic forces of acceleration. Static forces include gravity, while dynamic forces can include vibrations and movement. Hence, accelerometers are useful for sensing vibrations in systems or for orientation applications.

The accelerometer, or any other sensor, within the IMU 28 is adapted to communicating over an analog, digital, or pulse-width modulated connection interface in the IMU.

In an application level, the accelerometer, or other sensor in the IMU 28, is adapted to return multi-dimensional arrays of sensor values for each application programming interface call. For example, during a single sensor event the accelerometer returns acceleration force data for the three coordinate axes, and the gyroscope returns rate of rotation data for the three coordinate axes. These data values are returned in a float array (values) along with other IMU parameters.

In a preferred embodiment, the IMU framework uses a standard 3-axis coordinate system to express data values. For most sensors, the coordinate system is relative to the body frame that is defined relative to the screen of the wearable device or smart device 12 when the device is held in its default orientation. When a device is held in its default orientation, the X axis is horizontal and points to the right, the Y axis is vertical and points up, and the Z axis points toward the outside of the screen face. In this system, coordinates behind the screen have negative Z values. These axes are not swapped when the device's screen orientation changes-that is, the sensor's coordinate system never changes as the device moves. In another embodiment, a coordinate system relative to the global frame may be used.

In another embodiment, the IMU 28 provides a temperature compensation module to increase accuracy in dead reckoning situations.

On the other hand, gyroscopes are devices that measure or maintain rotational motion. MEMS (microelectromechanical system) gyroscopes are small, inexpensive sensors that measure angular velocity. Angular velocity is simply a measurement of speed of rotation. In one embodiment, the measurement unit of the gyroscope sensor is radiant per squared second (rad/s ²) . The gyroscope sensor of the IMU 28 of an embodiment of the present invention can also be used to determine orientation and are found in most autonomous navigation systems.

Preferably, the accelerometer and gyroscope sensors may be used at the beginning of the positioning process to align and calibrate the accelerometer and gyroscopes. External RF beacon signals are received and use for aiding in this process, such as to determine an initial reference position of the tracking device 20.

When alignment and calibration is completed, the accelerometer and gyroscopes data is then integrated into the RF beacon signals to determine the velocity and position of the wearable device or smart device 12.

The magnetometer sensor of the IMU 28 of the preferred embodiment of the present invention is a device adapted to detecting the Earth’s magnetic field along three perpendicular axes X, Y and Z. The Hall-effect sensor produces voltage which is proportional to the strength and polarity of the magnetic field along the axis each sensor is directed. The sensed voltage is converted to digital signal representing the magnetic field intensity. The magnetometer readings are reported in micro Tesla units (μT) .

Optionally, the IMU 28 of an embodiment of the present invention may also comprise an altimeter or barometric pressure sensors. An altimeter or barometric sensor is adapted to measuring the absolute pressure of the air around them. This pressure varies with both the weather and altitude. In one embodiment, the IMU 28 comprises a temperature compensation module to increase accuracy in determining the atmospheric pressure.

In another preferred embodiment of the present invention, the IMU 28 may also comprise other motion sensors, position sensors, and environment sensors. For example, the IMU 28 in one embodiment comprises a step counter for counting the number of steps taken by the user since the last reboot while the sensor was activated. Other sensors such as ambient temperature sensor, light sensor, and relative humidity sensor may also be available on the IMU 28. Alternatively, the accelerometer and/or the gyro-sensor may operate as a step counter with a suitable step counting algorithm.

The positioning circuit 20 of an embodiment of the present invention comprises a RF Unit 26 for processing RF signals broadcasted by RF beacons and other RF devices. In one embodiment, the RF Unit comprises a Bluetooth Low Energy (BLE) module with microcontroller for processing signals from BLE Beacons 14.

In an embodiment of the present invention the RF Unit 26 provides a two-way wireless link for the wearable device or smart device to communicate with a smart device 10. It is used to send the inertial sensors data to an app for data processing.

The smart device 12 of an embodiment of the present invention can be any smart phone with built-in RF or BLE technology and is capable of running application specific app. The smart device is the core for the navigation system. The inertial sensors together with ambient BLE-beacon signals provide the necessary data for the app to estimate the user real-time position and velocity.

The indoor navigation system 10 of the present invention comprises one or more of RF or BLE-beacons 14. In other embodiments, Wi-Fi Beacons or LED Beacons may be implemented. One or more of these RF or BLE Beacons 14 are installed inside the indoor infrastructure or enclosed environment. The small, usually battery-operated, RF or Bluetooth transmitter emits signals that the app uses to calculate a position that is accurate to 1 meter. The BLE technology enables battery operation over two years without having to access an external power supply. It works with almost all current operating systems.

In one preferred embodiment, the RF Beacon uses the BLE device for data transmission. The BLE device is set to run in broadcasting mode or advertising mode only. Each BLE device that broadcast packets using an agreed protocol is contain a data packet including a fingerprint or identifier and a location data. In one implementation, the data packet comprises: a Universally Unique Identifier (UUID) , a major value, and a minor value. The UUUID is a 128 bit value that identifies a beacon region. The major value is a 16-bit unsigned integer that can be used to group related beacons that have the same proximity UUID. The minor value is a 16-bit unsigned integer that differentiates beacons with the same proximity UUID and major value.

The BLE devices typically broadcast data at fixed intervals for a short duration. These BLE devices can be calibrated signal strengths at a predetermined covering distance, allowing receiving devices to estimate distances to transmitters and to obtain beacon positions via externally maintained databases. The smaller the covering distance will provide a better accuracy to the location data. However, more BLE devices are required to cover the same area. Typically, the covering distance is set to 1 meter to facilitate the calculation.

In one embodiment, the location data is a reference location. When a smart device 12 receive the reference location, it will communicate to a server 16 to retrieve the location matrix or coordinate data for further processing as shown in Fig. 1. In another embodiment, the smart device 12 has the mapping information stored in the memory. An installed software application can search the location matrix or coordinate data from the mapping information stored in the smart device 12. When the smart device 12 listens to BLE broadcast in a background service, estimating and relaying aggregated BLE device distance estimates and corresponding beacon identifying information to a central server at fixed intervals. These distance values are estimated derived from the strengths of the received signal strengths and the strengths of the calibrated signal strengths at the covering distance.

After the smart device 12 derives the estimated beacon distance, it will further assign a certain weight to each estimated distance such that larger distance estimates (which are inherently more noise- prone) have less bearing on the final position estimate. The optimal weighting. The data is then use to search for an instantaneous position.

In one implementation, the major value and the minor value are encrypted data such that it is difficult for foreign device to hijack the signals. In one embodiment the major value and the minor value comprises a public key and an encrypted reference using the corresponding private key or hash value. When the smart device 12 receives the signal it can use the public key and the encrypted message or hash to verify the authenticity of the broadcast signal and sent the encrypted message back to the server to retrieve the location information.

In another embodiment, the BLE device 14 is configured to broadcast a series of location reference in cycle. For example, the BLE device number 1 broadcast it is at 0 meter distance from region 1. Then it broadcasts another signal indicating that it is at 1.5 meter from region 2. Then it broadcasts another signal indicating that it is at 1.3 meter from region 3. When the smart device 12 receives the cyclic broadcast signals from two or more BLE device, it can cross reference the signal in order to detect any error, tempering or hacking in the BLE device 14.

In another embodiment, the server 16 is adapted to create a secure channel to communicate with the BLE devices 14. The server 16 will provide a time sensitive encryption key for the BLE devices 14 to encrypt the broadcast signals. When a smart device 12 received the broadcast signal, it can verify the currency and validity of the data with the server 16. As the encryption key is time sensitive, the server 16 can detect whether the encrypted data is current or obsolete.

In one implementation of the present invention, the inertial sensors of the IMU 28 may provide adequate data to estimate the relative position in real-time basis (with reference to an origin) . This relative position typically can be used as a reference for calibration. To combine the relative position coordinates with pre-determined ambient RF or BLE beacon 14 signal fingerprints, the smart device 12 can plot the absolute real-time position onto a digital map and provide navigation instructions.

Reference is now made to Fig. 3 in which an inertial navigation process of a preferred embodiment of the present invention is disclosed. The inertial navigation process relies on the three-axis accelerometer, three-axis gyroscope and three-axis magnetometer of the IMU 28 in a wearable device or smart device 10 to estimate the velocity and heading angles of the user.

As can be seen from Fig. 3, the accelerometer 32, gyroscope 34, and magnetometer 36 will take a current measure to calibrate the device’s noise.

After that, the indoor navigation system 10 will proceed to estimate the velocity based on the tri-axial accelerometer data and, meanwhile, the heading angles 48 by using some sort of algorithm which is to be determined. In this process, the accelerometer data and the gyroscope date are integrated to derive the carry position 42 of the indoor wearable device or smart device 12.

In the embodiment of the present invention, the altitude or floor change 44 is estimated based on the characteristic that the atmospheric pressure measured by the barometer decreases as the altitude increases.

In the present invention shown in Fig. 3, the accelerometer data, gyroscope data, and the magnetometer data are integrated to derive an altitude estimate filter 46. This altitude estimate filter 46 combined with the carry position 42, user activity, and accelerometer data is used to determine the heading angle 48 of the wearable device or smart device 10.

Alternatively or optionally, other filter such as Kalman filter may be incorporated to enhance the accuracy of the position or motion detection based on the measurements observed by one or more of these sensors repeatedly and periodically during the operation of the tracking device.

In one embodiment as shown in Fig. 3, the accelerometer data can also be used for deriving the number of steps taken 52 and estimate the stride length 54. In another embodiment, the IMU 28 comprises a step meter for counting the steps taken.

Based on the physiological characteristics of people, the waveform of the three-axis accelerometer modulus values describes the cyclical changes. The cyclical changes can be then used to detect the steps of people as well.

The estimated indoor position 56 of the wearable device or smart device can be derived by the altitude or floor change estimation 44, heading angle 48, and the stride length 54.

The inertial navigation process may be summarized as follows:

1. Inertial sensors calibration

2. Body placement detection (starting point of navigation) using Bluetooth beacon signals

3. User activity mode detection

4. Foot-step detection

5. Variable stride length model and calibration

6. Attitude estimation

7. Velocity estimation

8. Position update logic

9. Plotting of position on digital map

10. Generation of navigation information

In one embodiment, the above steps are carried out in a software application on the smart device 12. In another embodiment, a plurality of the above steps are carried out in a microelectromachanical system (MEMS) .

The Inertial navigation of an embodiment of the present invention is a self-contained navigation technique in which measurements provided by accelerometers and gyroscopes are used to track the position and orientation of an object relative to a known starting point, orientation and velocity. Inertial measurement units (IMUs) 28 typically contain three orthogonal gyroscopes and three orthogonal accelerometers, measuring angular velocity and linear acceleration respectively. By processing signals from these devices, it is possible to track the position and orientation of a device.

Using the measurements taken from the three-axis accelerometers and three-axis gyros, the inertial navigation system (INS) keeps track of where it is in three-dimensional space. The inertial navigation system derives the current position using a process called dead reckoning. The actual process of dead reckoning involves taking information from some source (gyros and accelerometers in this case) and turning them into a movement that can be added to the last known position to derive the current location.

Referring to Fig. 4, there is provided an algorithm for the strap down inertial navigation process 100. After the smart device 12 receives the broadcast signals from the BLE devices 14, the smart device 12 is able to retrieve an initial location from the server 16. The smart device 12 then performs the strap down inertial navigation algorithm to refine the current location.

In the strap down inertial navigation process 100, the smart device 12 first derives the orientation 101 with the gyroscope signals through the process 105. In the process 105, the orientation is tracked by integrating the angular velocity signal from the gyroscope on the IMU 28. As the gyroscope data is relative to the body frame, the smart device 12 will convert the data in relative to the global frame. The attitude of the smart derives 12 at the time interval t can be derived from the following equation:

where C(O) is the initial attitude of the smart device 12 which can be obtained by the BLE beacon signals,

ω _b (t) is the angular velocity obtained from the gyroscope.

In one embodiment of the present invention, the IMU 28 stores the gyroscope readings or angular velocity on a memory register at each determined time interval. The smart device 12 is adapted to read the angular velocity value from the memory register at a time at which after a period of δt has lapsed from the last gyroscope reading is put on the memory register. The smart device 12 is configured such that the δt is limited to a very small range, that is the time interval between two gyroscope readings are left on the memory register is small.

In another embodiment, the IMU 28 provides a memory stack for storing the gyroscope readings or angular velocity values. The new data will be written at the top of the stack, and the old value will be pushed to the bottom of the stack. The smart device may access a series of historical readings at the same time.

In one embodiment of the present invention, the IMU 28 is adapted to provide angular velocity readings at a predetermined time intervals. As the smart device 12 cannot obtain an instance reading but rely on the sampling data on a particular time interval, the smart device 12 has to estimate the current attitude based on the sampling data. In one embodiment, assuming the time lapsed from the last reading δt is small and the attitude can be derived from the following equation:

which can be estimated as to:

where C (t) is the attitude of the smart device 12 at the time interval t which can be obtained by the BLE beacon signals,

As the initial attitude C (O) or C (t) of the smart device 12 can be obtained from the BLE devices, this method can greatly reduce the propagation errors intrinsic to the IMU 28. Further, as the initial attitude C (O) or C (t) of the smart device 12 can be obtained through two different approaches, these values can be compared to derive a better calibrating algorithm to reduce error.

The smart device 12 is adapted to calculate the position from the accelerometer signals from the IMU 28 with the following equations:

where s _g (O) is the initial position, v _g (O) is the initial velocity, α _g (t) is the acceleration relative to the global frame derived from the accelerometer reading α _b (t) with the formula α _g (t) = C (t) α _b (t) , and C (t) is derived from the gyroscope reading.

In one embodiment of the present invention, the IMU 28 stores the accelerometer reading on a memory register at each determined time interval. The smart device 12 is adapted to read the accelerometer value from the memory register at a time at which after a period of δt has lapsed from the last accelerometer reading is put on the memory register. The smart device 12 is configured such that δt is limited to a very small range, that is the time interval between two accelerometer readings are left on the memory register is small.

In another embodiment, the IMU 28 provides a memory stack for storing the accelerometer readings. The new data will be written at the top of the stack, and the old value will be pushed to the bottom of the memory stack. The smart device may access a series of historical readings at the same time.

As the smart device 12 cannot obtain an instance accelerometer reading but rely on the sampling data on a particular time interval, the smart device 12 has to estimate the current displacement based on the sampling data. In one embodiment, assuming the time lapsed from the last reading δt is small and the displacement can be derived from the following equation:

Reference is now made to Fig. 5 where a simplified 2D example of dead reckoning is shown. For 3D navigation, magnetometer and pressure sensor can provide the attitude information.

Referring to Fig. 5, the smart device 502 is stationary and aligned squarely to the image, with its x-axis pointing straight up. The image then shows three other positions and the information recorded by the sensors between them. In one embodiment, the smart device 502 would update its position tens or hundreds of times per second, but in this example, the position updates are only shown when key changes take place for ease of understanding.

So at time zero, the smart device 502 is stationary (and does not know where it is) .

In this example, the smart device 502 then records an acceleration of 5 m/s ² on the x-axis accelerometer for 1 second, which gives it a velocity of 5 m/s (or 18 km/h) . It then immediately comes to a complete stop-detecting an acceleration of -10 m/s ² for 0.5 seconds.

As no other measurements are registered on the other sensors, the strap down navigator can easily work out that the smart device 502 has moved 3.75m in the direction of the x-axis.

As soon as the smart device 502 stops at position update 1, the z-axis gyroscope detects a value of 90 °/s for 0.5 seconds; so it knows that the smart device 502 has just turned 45° in a clockwise direction.

As soon as that movement is complete the smart device 502 records an acceleration on the x-axis accelerometer. This time it’s 1 m/s ² for 10 seconds followed by -5 m/s ² for 2 seconds.

Using the same techniques as before, the smart device can work out that it has now moved 60 meters further on at a 45° angle from where it was at position update 1. This means the smart device’s position updates are relative to the last known position.

The last movement is different to previous ones. At position update 2, the smart device 502 has rotated so it has the same orientation as initially. When it moves towards position 3 however, the smart device 502 records that it is moving at an angle to its measurement axis (the IMU frame) -it’s moving backward and to the right at a bearing of 135°.

Because of this movement, acceleration is registered simultaneously on both the x-and y-axis. There is also no negative acceleration causing the smart device 502 to stop-so although the measurements on the accelerometers drop to zero after 1 second, the IMU 28 is able to derive that it still has a velocity. In this case, it’s moving at 7.07 m/s (about 25 km/h) , and position update 3 happens 1.5 seconds after the smart device 502 leaves position update 2. In that time the smart device 502 has covered 7.95 meters.

In one embodiment, the MEMS of the smart device 502 is capable of receiving a location data from the BLE devices in the surrounding such that it can calculate and cross reference the exact location of the smart device. The smart device 502 may provide a software application to retrieve a local map from the storage device or download a local map from the server 16 to the smart device. The smart device then displays the current map and along with the current location on the display of the smart device.

In another embodiment, the software application is adapted to receive a destination data from a user. The software application may also allow a user to search for a destination. The software application then calculates one or more route from a first location or current location to the destination, and displays the route on the display of the smart device 502.

In one embodiment, the software application is adapted to periodically direct the user to move along the route to the destination. The smart device 502 may periodically update the current location and the route in order to track the progress of the user navigating to the destination.

In one embodiment, the software application is adapted to detect the smart device has moved from an indoor environment to an outdoor environment. This can be achieved by receiving GNSS signals sufficient to derive the current location, and losing track of BLE device signs which are available indoor. When the software application detects the chance from the indoor environment to an outdoor environment, the software application will switch from the indoor navigation system to a GNSS. Similarly, when the software application detects the chance from the outdoor environment to an indoor environment, the software application will switch from the GNSS to an INS.

With reference to Figure 6, in one example embodiment, the tracking device 20 is arranged to receive and process RF signals radiated from one or more beacon devices, such as a Bluetooth beacon or a BLE beacon. For example, the wireless module or the RF unit 26 may include a Bluetooth module capable of determining distances from the beacon devices. By processing the parameters or attributes of the RF signals such as the propagation time of the signal and/or the strength of the signal, the distance between the beacon and the device may be determined or estimated.

In this example, Bluetooth beacons 64 may be designed to be omni-directional, i.e. the beacons 64 radiate RF signals in all directions. Omni-directional antennas cover a space or an area in which the transmissions from nearby beacons can overlap.

Referring to Figure 6, the device 20 receives data at an overlapping area of two beacons 62 each including an omni-directional antenna which emit beam at all directions. The receiver 20 is located in the vicinity of both beacons radio coverage, and the determination of the location of the tracking device 20 may not be very accurate in some occasions due to interferences and attenuations of the overlapping signals.

With reference also to Figure 7, if such omni-directional beacons 62 are acting as reference points for a location registration or navigation system, the smart device or the tracking device 20 may not readily differentiate whether it is located at

positions

①, ② or ③, because any tracking device at either

locations

①, ② or ③ will receive the same identity information broadcasting by the beacon 62.

In an alternative embodiment, with reference to Figure 8, Bluetooth beacons 82 may be uni-directional. The signal sources may radiate RF signals which do not overlap with each other.

For example, each of the Bluetooth beacons 82 may include a directional antenna which radiates or receives signals in specific directions and thus enhancing the range and accuracies of position determination and reduced interference from unwanted sources.

Preferably, beacons 82 using directional antenna may be included in the system and operate as reference points for a location registration or navigation system. With reference to Figure 9, the tracking device 20 may identify its location at position ③ precisely. On the other hand, it the tracking device 20 is at either

location

① or ②, the smart device 20 would not receive any identity information from the beacon 82. Thus, using beacons with directional antenna as reference points will improve the accuracy for our location registration or navigation applications.

In some example embodiments, the navigation purely based on IMU and other sensors may encounter errors due to possible interference of signals induced by the environment and/or false detections due to imperfect conditions of the tracking device in practical usage scenarios. Periodical resetting the tracking process based on IMU sensors may be necessary to correct the determination of the position from time to time when the user tracks his movement in the indoor environment.

Preferably, beacons may be installed in desire positions in an indoor environment at a predetermined interval such that the beacons cover a reasonable coverage within the environment. Alternatively, beacons may be installed at selected positions such as a corner of a path or an exit in premises for location registration. Upon a detection of signal emitted from beacons, the tracking device may then reset or restart the entire process by determining the renewed/updated initial position of the device and then continue to track the movement of the user based on the detection results obtained by the motion sensors and/or the barometer/pressure sensors.

By combining both the dead reckoning method and the frequently updated positions of the tracking device based on the beacons, the navigation process may be significantly improved and thereby eliminate the possible false detection based on the non-perfect motion sensors in the tracking device. This may also allow using sensors with lower precisions so as to improve the cost effectiveness of the system.

These embodiments may be advantageous in that navigation information be provided to user of the tracking device moving within an indoor area or with in a building, in which satellite-based positioning system does not work well. Combining the movement detection and the reference position determination technology, current positions of the user may be updated in a real-time manner.

Advantageously, the system may assist user with visual impairment to navigate within a building such as a shopping mall or a hospital without much help from others, and therefore the user may no longer need to rely only on the tactile path paved on the ground.

In addition, by using uni-directional beacons or signal sources, position determination based on the beacon signals may be more efficient thus may further improve the accuracies of both the initial position determination as well as subsequent error corrections step during the tracking process.

Although not required, the embodiments described with reference to the Figures can be implemented as an application programming interface (API) or as a series of libraries for use by a developer or can be included within another software application, such as a terminal or personal computer operating system or a portable computing device operating system. Generally, as program modules include routines, programs, objects, components and data files assisting in the performance of particular functions, the skilled person will understand that the functionality of the software application may be distributed across a number of routines, objects or components to achieve the same functionality desired herein.

It will also be appreciated that where the methods and systems of the present invention may be either wholly implemented by computing system or partly implemented by computing systems then any appropriate computing system architecture may be utilised. This will include stand alone computers, network computers and dedicated hardware devices. Where the terms “computing system” and “computing device” are used, these terms are intended to cover any appropriate arrangement of computer hardware capable of implementing the function described.

It will be appreciated by persons skilled in the art that numerous variations and/or modifications may be made to the invention as shown in the specific embodiments without departing from the spirit or scope of the invention as broadly described. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive.

Any reference to prior art contained herein is not to be taken as an admission that the information is common general knowledge, unless otherwise indicated.

Claims

A tracking device comprising

a wireless module for receiving location reference from an external wireless device, and determine distances from the external wireless devices;

an inertial measurement unit (IMU) having an accelerometer for obtaining an acceleration vector and a gyroscope for obtaining an angular velocity vector;

a processing unit for determining a first estimated coordinate relative to a global frame from the location reference, calculating a second estimate coordinate relative to the global frame with the acceleration vector, the angular velocity vector, and the ambient atmospheric pressure.
A tracking device according Claim 1, wherein the IMU further comprises a magnetometer for measuring a magnetic field vector of an external magnetic field and/or a pressure sensor for obtaining an ambient atmospheric pressure.
A tracking device according any one of Claims 1 to 2, wherein the IMU is adapted to carry out self-calibration for the accelerometer and gyroscope.
A tracking device according any one of Claims 1 to 3, wherein the IMU comprises a step counter for counting a number indicating of steps moved thereof.
A tracking device according to Claim 5, wherein the IMU is adapted to derive a stride length by integrating the acceleration vector and the number of steps.
A tracking device according to any one of Claims 1 to 5, wherein the processing unit is adapted to derive an estimate attitude relative to the global frame with the angular velocity vector obtain from the IMU.
A tracking device according to any one of Claims 1 to 6, wherein the processing unit is adapted to derive an estimate displacement vector relative to the global frame with the angular velocity vector obtain from the IMU and the acceleration vector from the IMU.
A tracking device according to any one of Claims 1 to 7, wherein the processing unit is adapted to derive the second estimate coordinate with the displacement vector and the first estimate coordinate.
A tracking device according to any one of Claims 1 to 8, wherein the processing unit is adapted to forward the second estimate coordinate to a computer processor, wherein the computer processor is adapted to generate a relative current position on a local map.
A tracking device according to Claim 9, wherein the computer processor is associated with a display screen to display the local map and the relative current position and the local map on the display screen.
A tracking device according to Claim 10, wherein the computer processer is adapted to generate navigation information to display on the display screen.
A tracking device according to Claim 9, wherein the computer processor is associated with a speech module to play the navigation information in an audible format on a speaker.
A tracking device according to any one of Claim 9 to 12, wherein the computer processor is configured on a smart device.
A tracking device according to Claim 13, wherein the smart device is any one of the smart phone, handheld tablet, laptop computer, desktop computer, Electronic Positioning System, vehicles, aircraft, drone, robot, vessel, and biomechanical device.
A tracking device according to any one of Claim 1 to 14, further comprising a hardware interface to electrically connected to the computer processor.
A tracking device according to any one of Claim 1 to 15, comprising means for installing on a wearable device.
A tracking device according to Claim 16, wherein the wireless module is adapted to communicate with a wireless communication module electrically connected to the computer processor.
A tracking device according to any one of Claims 1 to 17, wherein the wireless module is adapted to communicate with the wireless device through a wireless protocol.
A tracking device according to Claim 18, wherein the wireless protocol is any one of Bluetooth protocol, Wi-Fi protocol, and Li-Fi protocol.
A tracking device according to any one of Claim 1 to 19, wherein the location reference is embedded in a data packet comprising a universal unique identifier (UUDI) of the wireless device and a data payload.
A tracking device according to Claim 20, wherein the data packet is broadcast by the wireless device at a predetermined time cycle.
A tracking device according to Claim 21, wherein the wireless device is configured to broadcast a plurality of data packet in one predetermined time cycle, wherein each data packet comprises the UUDI of the wireless device and a different location reference in the payload.
A tracking device according to any one of Claims 20 to 22, wherein the data payload is encrypted.
A tracking device according to any one of Claim 1 to 23, wherein the wireless device is adapted to communicate with a server through a secured channel, such that the server is adapted to configure the wireless device remotely.
A tracking device according to any one of Claims 9 to 24, wherein the processing unit is adapted to forward the location reference to the computer processor, wherein the computer processor is adapted to retrieve a global coordinate from a location database with the location reference.
A tracking device according to Claim 25, wherein the location database is installed on a server.
A tracking device according to Claim 26 wherein the computer processor is associated with a network module to communicate with the server through a network.
An indoor navigation method using a tracking device, and one or more wireless device, comprising the steps of:

receiving location reference from the one or more wireless devices, and determine distances from the devices;

determining a first estimated coordinate relative to a global frame from the location reference, obtaining an acceleration vector via an accelerometer of an inertial measurement unit (IMU) of the tracking device,

obtaining an angular velocity vector via a gyroscope of the IMU, and

calculating a second estimate coordinate relative to the global frame with the acceleration vector, the angular velocity vector, and the ambient atmospheric pressure.
An indoor navigation method according Claim 30, further comprising the step of:

obtaining a magnetic field vector of an external magnetic field via a magnetometer for measuring on the IMU; and/or

obtaining an ambient atmospheric pressure via a pressure sensor of the IMU.
An indoor navigation method according to Claim 28 or Claim 29, further comprising the step of performing self-calibration for the accelerometer and gyroscope.
An indoor navigation method according to Claim 28 to 30, further comprising the step of obtaining a value indicating steps moved via a step counter of the IMU.
An indoor navigation method according to Claim 31, comprising the step of deriving a stride length by integrating the acceleration vector and the number of steps.
An indoor navigation method according to any one of Claims 28 to 32, comprising the step of deriving an estimate attitude relative to the global frame with the angular velocity vector obtained from the IMU.
An indoor navigation method according to any one of Claims 25 to 33, comprising the step of deriving an estimate displacement vector relative to the global frame with the angular velocity vector and the acceleration vector.
An indoor navigation method according to any one of Claims 28 to 34, comprising the step of deriving the second estimate coordinate with the displacement vector and the first estimate coordinate.
An indoor navigation method according to any one of Claims 28 to 35, comprising the step of forwarding the second estimate coordinate to a smart device, wherein the smart device is adapted to generate a relative current position on a local map.
An indoor navigation method according to Claim 36, wherein the smart device is associated with a display screen to display the local map and the relative current position and the local map on the display screen.
An indoor navigation method according to Claim 37, wherein the smart device is adapted to generate navigation information to display on the display screen.
An indoor navigation method according to Claim 36, wherein the smart device is associated with a speech module to play the navigation information in an audible format on a speaker.
A tracking device according to Claim 1, wherein the wireless module is further arranged to determine distances from at least one beacon device.
A tracking device according to Claim 40, wherein the beacon device includes a Bluetooth beacon.
A tracking device according to Claim 40, wherein the beacon device is arranged radiate uni-directionally.
A tracking device accordance to Claim 42, wherein the beacon device comprises a uni-directional antenna.