CN103616729A - UWB bio-radar-based multiple-human body object estimation method and system - Google Patents

Abstract

The invention discloses a method and system for estimating multiple human targets based on UWB biological radar, which belongs to the technical field of biological radar life detection. In the processing of collected echo data, the invention firstly adopts breathing detection in each channel Algorithm, adaptive cancellation method and target recognition algorithm are used for processing, and then correlation processing is carried out between channels according to the processing results, and finally thresholds are set to remove residual clutter in the channel, and target classification and number estimation are realized at the same time. The method for estimating the number of human targets of the present invention lays a technical foundation for further realizing the biological radar detection and positioning of multiple human targets, and helps to improve the level and ability of biological radar technology to obtain human body information.

Description

A kind of a plurality of human body target evaluation methods and system based on UWB bioradar

Technical field

The invention belongs to bioradar human life detection field, be specifically related to a kind of a plurality of human body target evaluation methods and system based on UWB bioradar.

Background technology

Bioradar is a kind of special Radar Technology for life entity target detection and identification.This technology mainly be take human body as the detection of a target, and the electromagnetic wave of radar emission of take obtains the information of human body target as carrier.Its maximum advantage is the ability that possesses barriers such as penetrating wall, ruins, therefore in fields such as national security, emergency management and rescue, is with a wide range of applications.

In actual applications, people first pay close attention to whether someone exists, whether have at least people to exist.Therefore bioradar technology be take the detection of single target substantially as main present stage.Along with the realization of this technology, people can further pay close attention to the quantity of human body target, have on earth how many people to exist.Such as search after the earthquake ruins, press down the survivor who buries, counterterrorism operations mid-board monitors the terrorist in buildings etc.But up to the present, still do not have method to address this problem, particularly without any priori in the situation that.

Summary of the invention

The object of the present invention is to provide a kind of a plurality of human body target evaluation methods and system based on UWB bioradar, the method, based on many antennas UWB bioradar system, can accurately estimate human body target number under the condition that does not possess priori.

The present invention is achieved through the following technical solutions:

A plurality of human body target estimating systems based on UWB bioradar, comprise radar host computer, aerial array and computing machine, and described radar host computer comprises pulse producer, transmitter, central controller, chronotron and several receiving elements; Described aerial array comprises 1 emitting antenna and 3 receiving antennas, and emitting antenna is connected with the transmitter of radar host computer, and each receiving antenna and a receiving element are connected to form a radar return data channel; Described receiving element comprises receiver and the analog to digital converter being connected with receiver, and the output terminal of each analog to digital converter is all connected with central controller, and central controller is realized and being communicated by letter with computer interactive;

Pulse producer produces periodic short pulse signal: a part is delivered to transmitter shaping, then by emitting antenna, radiate; Another part narrow pulse signal is sent to chronotron and produces control signal, and triggers receiving element and echoed signal is carried out in distance to selectivity reception.

Described aerial array adopts linear array arrangement mode, centered by emitting antenna, the adjacent setting of the first receiving antenna and emitting antenna, the second receiving antenna and the 3rd receiving antenna are symmetricly set in respectively the both sides of emitting antenna, and the distance of the second receiving antenna, the 3rd receiving antenna and emitting antenna is 0.3～1m.

Described each independently echo data interchannel employing reinforcement isolated from power design.

UWB bioradar adopts impulse system, and exomonental width is controlled at ns rank, and corresponding spectrum width and centre frequency are 500MHz; Emitting antenna and receiving antenna all adopt butterfly dipole antenna, and with radar host computer between use shielding coaxial cable to be connected.

A plurality of human body target evaluation methods based on UWB bioradar, comprise the following steps:

1) data acquisition

After several radar return data channel samplings of UWB bioradar system, the echo data obtaining is delivered to computing machine and carry out Storage and Processing;

2) in passage, process

First, to the echo data obtaining, adopt breathing detection algorithm to obtain human body respiration signal; Secondly, to the human body respiration signal detecting, adopt adaptive cancellation method to suppress the phase mutual interference of breath signal between different human body target; Finally, by Target Recognition Algorithms, setting energy threshold identifies target individual;

3) interchannel is processed

To step 2) waveform corresponding to human body target identification point in each passage of recognizing calculate interchannel correlation coefficient r according to formula (1) _ij:

$r_{\mathrm{ij}}=\frac{{\mathrm{\ΣS}}_i{S}_j}{{\left[\mathrm{\Σ}{S}_i^2\mathrm{\Σ}{S}_j^2\right]}^{1/2}}---\left(1\right)$

Wherein, S _iand S _jrepresent the waveform on two passages, i wherein, j=1,2,3 ..., and i ≠ j;

Setting threshold A, by the correlation coefficient r calculating _ijcontrast with this threshold value A, carry out the differentiation of different target: for the impact point in each channel recognition result, must exist another passage impact point and its related coefficient to be greater than the threshold value A of this setting, otherwise be considered as clutter; The impact point that interchannel related coefficient is greater than the threshold value A of this setting is regarded as from same target;

4) last, the clutter in each passage is removed, by target classification, obtain human body target number.

Step 2) described breathing detection algorithm is specially:

First, the range information providing according to UWB bioradar system, in the enterprising line slip average treatment of distance, improves the signal to noise ratio (S/N ratio) of echo data to echo data;

Secondly, remove time-independent static background clutter in echo data;

Again, utilize the narrow-band characteristic of human body respiration, adopt adaptive algorithm that human body respiration is carried out separated with noise;

Finally, according to the gradual feature of human body respiration, carry out low-pass filtering, obtain the human body respiration signal that detections of radar arrives.

Step 2) described adaptive cancellation method is using the waveform of a certain range points in the echo data after breathing detection algorithm process as input signal, before this range points, the breath signal of human body target, as with reference to signal, obtains coefficient that error signal remove revise sef-adapting filter after subtracting each other with two paths of signals; If input corresponding a certain target range point signal, this flow process can offset the hangover of previous targets and disturb, and exports the breath signal of this target; If input signal is the hangover that previous targets respiratory movement causes, after offseting, output signal is zero; Wherein, described sef-adapting filter adopts LMS algorithm to realize.

Step 2) described Target Recognition Algorithms is that the data of processing through the method for adaptive cancellation are accumulated in time, obtain the energy-range distribution of one dimension, in this distribution, in human body target respective distances, there will be energy peak, this energy peak setting threshold is had to aimless binary judgement, can identify target.

First, set energy threshold Th1 and dependent thresholds Th2;

Energy threshold Th1 has driftlessness for judgement, chooses impact point ENERGY E _obj, clutter point ENERGY E _clu, work as E _obj/ E _cluwhile being greater than energy threshold Th1, judging in this range points for target and be output as 1, otherwise exporting 0;

Dependent thresholds Th2 is used for choosing clutter point, and the point that energy maximum and waveform and impact point waveform correlation coefficient are less than dependent thresholds Th2 except impact point in recognition window is regarded as clutter point, and this energy is as E _clu.

Described energy threshold Th1 and dependent thresholds Th2 are empirical value, and Th1=2, Th2=0.6.

Compared with prior art, the present invention has following useful technique effect:

Radar antenna array of the present invention is comprised of 1 emitting antenna and 3 receiving antennas, and the receiving element that each receiving antenna is corresponding with it has formed 3 independently radar return data channel.For same target, the breath signal that different passages detect has high correlation; And for breath signal and the clutter of different target, each interchannel degree of correlation is lower.Therefore the present invention is on to the processing of the echo data collecting, first in each passage, adopt breathing detection algorithm, adaptive cancellation method and Target Recognition Algorithms to process, then according to this result, at each interchannel, carry out relevant treatment, last setting threshold is removed in passage and is processed residual clutter, and realize target classification simultaneously and number are estimated.The evaluation method of human body target number of the present invention, in order further to realize, the bioradar of a plurality of human body targets is surveyed and technical foundation has been established in location, contributes to promote level and the ability that bioradar technology is obtained human body information.

Further, UWB bioradar of the present invention adopts impulse system, and exomonental width is controlled at ns rank, and corresponding spectrum width and centre frequency are 500MHz, can guarantee penetration capacity and the detectability to human body respiration simultaneously.

Accompanying drawing explanation

Many antennas of Fig. 1 UWB bioradar system chart;

Echo Processing process flow diagram in Fig. 2 passage;

UWB bioradar echo data after Fig. 3 breathing detection algorithm process;

Fig. 4 interference suppression algorithm schematic diagram;

Fig. 5 passage internal object recognizer schematic diagram

Fig. 6 passage internal object recognition result

The human body target that the different passages of Fig. 7 detect is breathed and clutter;

Two human body targets that the different passages of Fig. 8 detect are breathed;

The clutter that the different passages of Fig. 9 detect;

Figure 10 interchannel treatment scheme;

Figure 11 efficiency evaluation experiment schematic diagram;

During Figure 12 driftlessness, many antennas UWB bioradar is surveyed and target number estimated result;

During Figure 13 single goal, many antennas UWB bioradar is surveyed and target number estimated result;

During Figure 14 Bi-objective, many antennas UWB bioradar is surveyed and target number estimated result;

During Figure 15 tri-target, many antennas UWB bioradar is surveyed and target number estimated result.

Embodiment

Below in conjunction with concrete drawings and Examples, the present invention is described in further detail, and the explanation of the invention is not limited.

Referring to Fig. 1, a plurality of human body target estimating systems that the present invention is based on UWB bioradar are mainly comprised of three functional modules: aerial array, radar host computer and computing machine.Pulse producer in radar host computer produces periodic narrow pulse signal, and a part is delivered to transmitter shaping, then by emitting antenna, radiate; A part is delivered to chronotron generation control signal triggering receiver and echoed signal is carried out in distance to selectivity reception.Chronotron adopts the design of digital multi-channel stepping technique, and full accuracy can reach 10ps.Aerial array is comprised of four unit: 1 emitting antenna and 3 receiving antennas, all adopt between butterfly dipole antenna and radar host computer and use shielding coaxial cable to connect.Each receiving antenna and a receiving element are connected to form a radar return data channel; Described receiving element comprises receiver and the analog to digital converter being connected with receiver.Each interchannel adopts strengthens isolated from power design, can effectively alleviate interchannel echoed signal coupling.Data after each channel sample are delivered to computing machine and are carried out Storage and Processing.Central controller is mainly used in communicating by letter of computing machine and radar host computer, realizes the function of parameter setting and data transmission, uses USB to connect between it and computing machine.

Because the present invention only relates to the estimation of human body target number, aerial array adopts linear array form, and concrete arrangement mode is: centered by emitting antenna; Receiving antenna 1 is positioned at one side and near its placement; Receiving antenna 2 and 3 lays respectively at emitting antenna both sides and is symmetrically distributed; With its centre distance be 0.3～1m, this lower limit determines by antenna size, the upper limit is relevant with antenna beamwidth.Radar transmitted pulse repetition frequency is 128KHz, and triple channel adopts synchronous data collection, and corresponding parameter is as shown in table 1.

Table 1UWB bioradar key job parameter

Time window	80ns
		Reference position	5ns
Sampling number	8192
		Sweep velocity	16Hz

Below radar return data processing in a plurality of human body target evaluation methods based on UWB bioradar of the present invention is elaborated:

One, in passage, process

As shown in Figure 2, be the basic procedure of processing in UWB bioradar passage, each passage echo data all adopts this flow process to process.In passage, process and formed by three key steps: breathing detection algorithm, interference suppression algorithm and Target Recognition Algorithms.Breathing detection algorithm is mainly realized the detection of human body respiration signal; Adopt on this basis adaptive cancellation to suppress the phase mutual interference of breath signal between human body target; Because human body target breathing causes energy in its respective distances, increase, finally set energy threshold target is identified.

1. breathing detection algorithm

Comprise following functional module: signal to noise ratio (S/N ratio) improvement, background removal, self-adaptation strengthen and low-pass filtering.Wherein, it is the range information that utilizes UWB bioradar to provide that signal to noise ratio (S/N ratio) is improved, and averages the signal to noise ratio (S/N ratio) that improves echo data in distance; Background removal is used for removing the time-independent static background clutter of radar return data, subtracts average realization on the employing time; Self-adaptation strengthens the narrow-band characteristic of utilizing human body respiration, and it is separated with broadband noise, thereby reaches the object of enhancing; Low-pass filtering adopts digital filter, leaches the human body low-pass signal of low frequency.

Referring to Fig. 3, be the UWB bioradar echo data after breathing detection algorithm process, wherein comprise the time and apart from two-dimensional signal, distance represents with pulse two way travel time ns.In these data, human body target, apart near 28ns, presents the periodic undulations of going up in time.Extract the wherein waveform of energy ultimate range point, can obtain the human body respiration signal of detections of radar.As can be seen from the figure,, owing to being subject to the modulation of human body respiration motion, UWB bioradar echo data presents obvious hangover.When radar is used for a plurality of target detection, the hangover meeting of previous targets forms and disturbs subsequent target, affects result of detection when serious.Therefore, it being suppressed is to realize the key that a plurality of human body target numbers are estimated.

2. interference suppression algorithm

Disturb and suppress treatment scheme as shown in Figure 4, wherein input signal is the waveform of a certain range points in the UWB bioradar echo data after breathing detection algorithm process, reference signal is this range points breath signal of human body target before, obtains error signal and remove to revise adaptive filter coefficient after two paths of signals subtracts each other.If input corresponding a certain target range point signal, this flow process can offset the hangover of previous targets, exports the breath signal of this target; If input signal is the hangover that previous targets respiratory movement causes, after offseting, output signal is zero.Sef-adapting filter adopts LMS algorithm to realize.

3. Target Recognition Algorithms

After above algorithm process, in UWB bioradar echo data in range points corresponding to target, because the effect of human body respiration can present stronger energy.These data are accumulated in time to the energy-range distribution that obtains one dimension, in this distribution, in human body target respective distances, there will be energy peak, its setting threshold is had to aimless binary judgement, can identify target.

Target Recognition Algorithms signal as shown in Figure 5, arranges threshold value Th1 and Th2, N in figure _winrepresent recognition window, it is relevant with the range resolution of system, adopts 2 times of distances corresponding to UWB radar pulse width (N that counts _win=8ns); E _objrepresent impact point energy; E _clurepresent clutter point energy.

Energy threshold Th1 has driftlessness for judgement, works as E _obj/ E _cluwhile being greater than energy threshold Th1, illustrate that impact point energy is significantly greater than clutter point energy, be the possibility of target very large (judge accordingly in this range points and have human body target in other words), judge in this range points for target and be output as 1, otherwise exporting 0.

Dependent thresholds Th2 is used for choosing clutter point, and following rule is observed in choosing of clutter point: in recognition window, except impact point, energy maximum and waveform and impact point waveform correlation coefficient are less than the point of threshold value Th2.

Wherein, the energy threshold Th1 of institute and dependent thresholds Th2 are empirical value, and Th1=2 represents to be significantly higher than clutter point because human body respiration causes impact point energy; Th2=0.6, it is low that related coefficient is less than these value representation two waveform degrees of correlation, and the probability that clutter point is correctly chosen is large.Concrete treatment step is:

First, ask the related coefficient of clutter point waveform and the impact point waveform of selection, then by this related coefficient and Th2 comparison, this related coefficient is greater than Th2=0.6, illustrates that both degrees of correlation are high, and the clutter point of selection and impact point similarity degree are higher, illustrate that now definite clutter point energy is incorrect, only have this related coefficient to be less than Th2=0.6, just illustrate that selected clutter point is exactly clutter point, impact point is exactly impact point.

As shown in Figure 6, this figure be certain data of surveying UWB bioradar system second channel collection in the experiment of two human body targets to Output rusults after Fig. 5 Target Recognition Algorithms is processed.Identified according to two human body targets at 14ns and 23ns place in the known figure of the priori of target range, but there is the residual clutter producing due to erroneous judgement in 68ns and 84ns place.For correct estimating target number, the interchannel of proceeding based on many antennas UWB bioradar is processed.

Two, interchannel is processed

Referring to Fig. 7, shown the many antennas UWB bioradar system that adopts the present invention to use, survey after a certain human body target the breath signal of 3 detected these human body targets of radar return data channel.As can be seen from the figure, 3 road respiratory waveforms are consistent, present very high degree of correlation.This is that because three receiving antennas independently receive and sample, so the breath signal detecting in different pieces of information passage in theory should be in full accord because of the echoed signal producing for same target.In figure, dotted line represents the clutter waveform in a certain passage range points, and it and respiratory waveform differ greatly, and degree of correlation is lower.

Fig. 8 has shown the breath signal detecting after two human body targets of many antennas UWB bioradar system detection that adopt the present invention to use, and both shape differences are larger.This is because different target respiratory rhythm always there are differences, and the respiratory waveform degree of correlation therefore detecting is lower.

Fig. 9 has shown two two-way noise signals that radar return data channel detects.Because clutter produces, there is certain randomness, add and derive from different pieces of information passage, the inevitable consistance that do not exist.

More than analyze and show, for many antennas UWB bioradar:

(1) breathing of the same target that different passages detect is height correlation;

(2) the breathing degree of correlation of the different target that different passages detect is lower;

(3) clutter and human body target breathing degree of correlation are low;

(4) degree of correlation between clutter is low.

Therefore consider to carry out relevant treatment at interchannel, can not only effectively remove clutter, thereby and can distinguish the estimation of human body target realize target number.

Figure 10 has shown the basic procedure that interchannel is processed, and first according to the result of 3 passage human body target identifications, calculates interchannel related coefficient, is about to waveform corresponding to impact point in each channel recognition result and calculates in pairs related coefficient at interchannel, and method is as follows:

$r_{\mathrm{ij}}=\frac{{\mathrm{\ΣS}}_i{S}_j}{{\left[\mathrm{\Σ}{S}_i^2\mathrm{\Σ}{S}_j^2\right]}^{1/2}}---\left(1\right)$

Si and Sj represent two waveforms on passage, i wherein, j=1,2,3 ..., and i ≠ j.

Setting threshold A, by the correlation coefficient r calculating _ijcontrast with this threshold value A, carry out the differentiation of different target, rule is as follows: (1), for the impact point in each channel recognition result, must exist another passage impact point and its related coefficient to be greater than this threshold value A, otherwise be considered as clutter; (2) impact point that interchannel related coefficient is greater than this threshold value A is regarded as from same target.

Correlation coefficient r _ij more approach 1 expression two waveform degrees of correlation higher, consistance is better.After above rule treatments, the residual clutter in each passage is removed, and target is classified simultaneously, thereby obtains target number.Threshold value A is an empirical value herein, and it is best that great many of experiments shows that this value is set as 0.6 o'clock performance.

By concrete contrived experiment, the usefulness of the inventive method is evaluated below:

As shown in figure 11, this UWB bioradar penetrates brick wall that a stifled 28cm is thick and surveys after to wall.Detection process comprises 4 kinds of situations: there is no target, 1 target (P1), 2 targets (P1, P2), 3 targets (P1, P2, P3).Wherein P1 is over against emitting antenna, is positioned at about 3m place after wall; 20 ° of the relative emitting antenna left avertences of P2, are positioned at about 4m after wall; 20 ° of the relative emitting antenna right avertence of P3, are positioned at about 5m after wall.While having target, each target face is stood to wall and is kept static.

Figure 12～15 have shown above-mentioned four kinds of results that situation is corresponding, and in figure, each row is distinguished respective channel 1,2 and 3 under upper; Each row are respectively the data after interference suppression algorithm is processed in passage, one dimension energy-range distribution that these data are corresponding, and human body target recognition result from left to right.In addition, after interchannel relevant treatment, the fork-shaped sign of the clutter point in each passage, the triangle sign of different directions for the target distinguishing.As can be seen from these figures, the target number identifying in 4 kinds of situations is with actual in full accord.Therefore,, without any priori in the situation that, the identification that the present invention is a plurality of human body targets of bioradar and number are estimated to provide a kind of effective method, contribute to promote level and the ability that bioradar technology is obtained human body information.

Should be understood that, for those of ordinary skills, can be improved according to the above description or convert, and all these improvement and conversion all should belong to the protection domain of claims of the present invention.

Claims (10)

1. A plurality of human body target estimation systems based on UWB biological radar, is characterized in that, comprises radar main frame, antenna array and computer, and described radar main frame comprises pulse generator, transmitter, central controller, delayer and Several receiving units; the antenna array includes 1 transmitting antenna and 3 receiving antennas, the transmitting antenna is connected to the transmitter of the radar host, and each receiving antenna is connected to a receiving unit to form a radar echo data channel; the The receiving unit includes a receiver and an analog-to-digital converter connected to the receiver, the output of each analog-to-digital converter is connected to the central controller, and the central controller interacts with the computer to realize communication; The pulse generator generates a periodic narrow pulse signal: one part is sent to the transmitter for shaping, and then radiated out through the transmitting antenna; the other part of the narrow pulse signal is sent to the delayer to generate a control signal, and triggers the receiving unit to adjust the distance of the echo signal for selective reception. 2. A kind of UWB biological radar system capable of estimating multiple human targets according to claim 1, wherein the antenna array adopts a linear array arrangement, with the transmitting antenna as the center, the first receiving antenna and the transmitting antenna Adjacent to each other, the second receiving antenna and the third receiving antenna are symmetrically arranged on both sides of the transmitting antenna, and the distance between the second receiving antenna, the third receiving antenna and the transmitting antenna is 0.3-1m. 3. A UWB biological radar system capable of estimating multiple human targets according to claim 1, characterized in that a reinforced power supply isolation design is adopted between said independent echo data channels. 4. A kind of UWB biological radar system capable of estimating multiple human targets according to any one of claims 1 to 3, characterized in that, the UWB biological radar adopts an impulse pulse system, and the width of the emission pulse is controlled at ns level , the corresponding spectrum width and center frequency are both 500MHz; both the transmitting antenna and the receiving antenna use a butterfly dipole antenna, and are connected to the radar host with a shielded coaxial cable. 5. A method for estimating multiple human targets based on UWB bioradar, characterized in that, comprising the following steps: 1) Data collection After sampling several radar echo data channels of the UWB biological radar system, the obtained echo data is sent to the computer for storage and processing; 2) In-channel processing Firstly, the breathing detection algorithm is used to obtain the human breathing signal for the obtained echo data; secondly, the adaptive cancellation method is used for the detected human breathing signal to suppress the mutual interference of breathing signals between different human targets; finally, through the target recognition algorithm Set the energy threshold to identify the target individual; 3) Inter-channel processing For the waveform corresponding to the human body target recognition point in each channel identified in step 2), calculate the correlation coefficient r _ij between channels according to formula (1): ${\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; \&Sigma;S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}}{{<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; ]</span>}^{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$ Among them, S _i and S _j represent the waveforms on two channels, where i, j=1, 2, 3..., and i≠j; Set the threshold A, compare the calculated correlation coefficient r _ij with the threshold A, and distinguish different targets: For the target points in the recognition results of each channel, there must be another channel target point with a correlation coefficient greater than the set The threshold A, otherwise it is regarded as clutter; the target points with the inter-channel correlation coefficient greater than the set threshold A are regarded as coming from the same target; 4) Finally, remove the clutter in each channel, classify the targets, and obtain the number of human targets. 6. A method for estimating multiple human targets based on UWB bioradar according to claim 5, characterized in that the breathing detection algorithm described in step 2) is specifically: First, according to the distance information provided by the UWB bio-radar system, the echo data is subjected to sliding average processing on the distance to improve the signal-to-noise ratio of the echo data; Secondly, remove the static background clutter in the echo data that does not change with time; Thirdly, using the narrow-band characteristics of human respiration, an adaptive algorithm is used to separate human respiration from noise; Finally, low-pass filtering is performed according to the slowly changing characteristics of human respiration to obtain the human respiration signal detected by the radar. 7. A method for estimating multiple human targets based on UWB bioradar according to claim 5, characterized in that the adaptive cancellation method described in step 2) is to use the echo data processed by the breathing detection algorithm The waveform of a certain distance point is used as the input signal, and the breathing signal of the human target before the distance point is used as the reference signal, and the error signal is obtained after subtracting the two signals to correct the coefficient of the adaptive filter; if the input corresponds to a certain target distance point signal, the process will cancel the trailing interference of the previous target, and output the breathing signal of the target; if the input signal is the tailing caused by the breathing movement of the previous target, the output signal will be zero after cancellation; wherein, the The adaptive filter is realized by LMS algorithm. 8. A method for estimating multiple human targets based on UWB bioradar according to claim 5, characterized in that the target recognition algorithm in step 2) is to process the data processed by the adaptive cancellation method in the Accumulate over time to obtain a one-dimensional energy-distance distribution. In this distribution, there will be an energy peak at the corresponding distance of the human target. Set a threshold for the energy peak to make a binary judgment of whether there is a target, and then the target can be identified. 9. A kind of method for estimating multiple human targets based on UWB biological radar according to claim 8, characterized in that, the binary judgment of whether there is a target refers to: First, set the energy threshold Th1 and related threshold Th2; the energy threshold Th1 is used to judge whether there is a target, select the energy E _obj of the target point, and the energy E _clu of the clutter point. When E _obj /E _clu is greater than the energy threshold Th1, then judge The distance point is the target and the output is 1, otherwise the output is 0; the correlation threshold Th2 is used to select the clutter point, and the point in the recognition window with the largest energy except the target point and the correlation coefficient between the waveform and the target point waveform is less than the correlation threshold Th2 is regarded as is a clutter point, and the energy of this point is taken as E _clu . 10. A method for estimating multiple human targets based on UWB bioradar according to claim 9, characterized in that: said energy threshold Th1 and related threshold Th2 are both empirical values, and Th1=2, Th2=0.6 .

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