CN110865376A - TBD-based non-direct-view corner human body target positioning method - Google Patents
TBD-based non-direct-view corner human body target positioning method Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
- G01S15/02—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems using reflection of acoustic waves
- G01S15/06—Systems determining the position data of a target
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/06—Systems determining position data of a target
- G01S13/46—Indirect determination of position data
- G01S2013/462—Indirect determination of position data using multipath signals
- G01S2013/464—Indirect determination of position data using multipath signals using only the non-line-of-sight signal(s), e.g. to enable survey of scene 'behind' the target only the indirect signal is evaluated
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- Radar, Positioning & Navigation (AREA)
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Abstract
The invention discloses a TBD-based non-direct-view corner human body target positioning method, which is applied to the field of hidden target detection and aims at solving the problem of high false alarm rate in the existing hidden target positioning; calculating the associated area of the points in the next frame, selecting the position of the point with the maximum amplitude in the associated area as the most probable position of the target point corresponding to the previous frame in the next frame, accumulating the amplitude of the position and the amplitude of the point corresponding to the previous frame, repeating the process, and accumulating until the preset period number; and finally, extracting peak values of amplitude accumulation results corresponding to all the points, backtracking according to the positions recorded before, and obtaining the real position of the target after trace point smoothing.
Description
Technical Field
The invention belongs to the field of hidden target detection, and particularly relates to a human target positioning technology in a non-direct-view corner scene.
Background
The technology for detecting the hidden target in the urban environment mainly utilizes the reflection of electromagnetic waves by buildings to detect, position and identify the hidden target in a non-line-of-sight range, and has great application value in the fields of anti-terrorism, public security law enforcement, disaster rescue and the like. Because there are a large amount of smooth wall bodies in the scene of city building turning, the electromagnetic wave can reflect and receive the radar again through the target reflection after once or many times after launching from the transmission radar on the wall body surface, or hit the target earlier, then reflect the wall again, reflect and receive the radar back at last, lead to the echo that the radar received very disorderly to it hides the target detection difficulty to have increased the building turning. Therefore, how to realize accurate positioning of the concealed target of the building corner under the condition of disordered multipath echo is a problem worthy of study.
At present, many researches on the detection of the hidden target of the building corner are carried out at home and abroad, and the Nanjing post and telecommunications university provides a three-step positioning algorithm to reduce the influence of NLOS (non-line-of-sight) propagation and achieve the ideal positioning precision of target tracking in the NLOS propagation environment. The method needs to set a plurality of base stations to realize the positioning of the target, only gives a simulation result, and actually measures the positioning effect to be verified. Aiming at the problem of corner target detection, the French Aerospace laboratory provides two detection and positioning methods (K. Thaiet al. detection-localization Algorithms inside arc-the-corner radar radio networks. IEEE Transactions on Aero space and Electronic Systems.), one method is to jointly process information provided by multipath return, and the other method is to incoherently integrate information from different paths so as to detect and estimate the NLOS target position. From the positioning result, although the position of the target can be detected, a plurality of false points are generated at the same time, and the false alarm rate is high. The above algorithms have many problems in practical application, the complexity of the detection device is increased by the multi-site arrangement, and many false targets are generated by high false alarms. Therefore, the research on the non-line-of-sight corner target positioning based on the millimeter wave radar has important value.
Disclosure of Invention
In order to solve the technical problems, the invention provides a non-direct-view corner human body target positioning method based on TBD (Track Before detection tracking), which can effectively position a target by utilizing primary multipath of electromagnetic waves in a non-direct-view corner scene and reduce interference caused by secondary and high-order multipath.
The technical scheme adopted by the invention is as follows: a non-direct-view corner human body target positioning method based on TBD comprises the following steps:
s1, pulse compression and incoherent accumulation are carried out on the collected radar echo data under the non-direct-view corner scene;
s2, setting initial values, specifically: setting the initial state as position information in two-dimensional directions of an x axis and a y axis, and taking the amplitude value of the first frame of observation data as an amplitude accumulation value of the first frame;
s3, determining the corresponding associated area of each frame;
s4, amplitude recursive accumulation, specifically: accumulating the amplitude according to the state of the current frame and the corresponding associated area;
s5, extracting a target peak value, specifically: when the Nth frame is accumulated, performing peak value extraction on the amplitude accumulation result to obtain an amplitude recursion accumulation result of the target;
s6, tracing trace points, specifically: according to the peak value extracted in the step S5, the positions of the distance units where the targets are located in all the accumulated frames in the step S4 are traced back, the real positions of the targets corresponding to the distance units are calculated, and target point trace estimation is obtained;
and S7, performing smoothing filtering on the target point trace estimation obtained in the step S6 to obtain a smoothed target point trace.
Further, step S3 is specifically: and determining a possible area of the next frame target according to the distance unit of the previous frame target, wherein the area is the relevant area corresponding to the next frame.
Further, the correlation area is determined by the moving speed of the target and the radar inter-frame sampling interval.
Further, the associated region corresponding to the next frame is a region formed by the distance unit where the target of the previous frame is located and a distance unit before and after the target of the previous frame.
Further, step S4 is specifically:
a1, taking the distance unit with the maximum amplitude of the previous frame in the correlation area of the current frame as the position of the target of the current frame;
and A2, adding the amplitude of the distance unit where the target is located determined in A1 and the amplitude of the distance unit where the target is located in the previous frame, and recording the distance unit where the target of the current frame is located.
The invention has the beneficial effects that: the hidden target positioning method based on TBD provided by the invention can effectively utilize primary multipath of electromagnetic waves under a non-direct-view corner scene to position a target, reduce interference caused by secondary multipath and high-order multipath, and especially improve the detection probability of the target, reduce the false alarm probability and greatly improve the positioning precision of the target when the primary multipath amplitude of the target echo is lower than the secondary multipath and the high-order multipath.
Drawings
FIG. 1 is a flow chart of a non-direct-view corner human body target positioning algorithm based on a TBD algorithm.
Fig. 2 is a process of association area determination.
Fig. 3 is a measured scene graph.
Fig. 4 is a target range image.
Fig. 5 shows the positioning result of the false alarm rate of 5.28%.
Fig. 6 shows the positioning result with the false alarm rate of 12.29%.
Fig. 7 shows the results of target positioning using the TBD method.
Fig. 8 shows the target positioning error using the TBD method.
Fig. 9 shows the positioning result after smoothing.
Fig. 10 shows the smoothed positioning error.
Detailed Description
In order to facilitate the understanding of the technical contents of the present invention by those skilled in the art, the present invention will be further explained with reference to fig. 1 to 10.
As shown in fig. 1, the implementation process of the present invention includes the following steps:
s1, pulse compression and incoherent accumulation are carried out on the collected radar echo data under the non-direct-view corner scene;
and carrying out fast time Fourier transform on the preprocessed echo data to obtain a pulse compression result. Because the transmitting interval of the radar signals is 1ms, the moving distance of the human body in 1ms when walking can be ignored, therefore, assuming that the target in 1ms is still, the incoherent accumulation is carried out on the echo signals of 128 periods, the signal to noise ratio is improved, the subsequent processing is facilitated, the obtained distance image is shown in fig. 4, the distance image is an L multiplied by M matrix, L corresponds to the distance dimension on the distance image, and M corresponds to the time dimension on the distance image.
The pretreatment is specifically as follows: and removing the zone bits of the acquired data, separating the data among different channels, eliminating the interference of a fixed target and facilitating subsequent processing.
S2, setting initial values, specifically: assuming that all range bins on the range image over the first accumulation period are the target locations, all locations and their corresponding amplitudes are recorded. Let initial state s (1) be position information in x-axis and y-axis two-dimensional directions, and be recorded as s (1) ═ rx(1),ry(1))，rx(1)、ry(1) Respectively representing the coordinates of the target on the x axis and the y axis, taking the amplitude value p (1) of the observation data of the first frame as the amplitude accumulation value f (1) of the first frame, and taking the backtracking function Ψ1(s (1)) is initialized to (0, 0).
S3, determining the corresponding associated area of each accumulation period;
let the maximum speeds of the targets in the x-axis and y-axis directions be vxmaxAnd vymaxThe radar inter-frame sampling interval is T, and the correlation area determination process is shown in fig. 2.
The dashed box in the figure is the region where the target of the current frame may appear, which is obtained from the previous frame, i.e., the associated region Γ (s (n)), and is calculated as follows:
in practical application, because the moving distance of the human body target in an accumulated frame is very small when the human body target normally walks, the moving distance does not exceed one distance distinguishing unit, and therefore the position of the target in the previous frame is within a distance unit which is plus or minus the position of the previous frame. For example, the previous frame object is at 178 range bin, then the next frame object should appear in 177-179 range bins.
S4, amplitude recursive accumulation, specifically: accumulating the amplitude according to the state of the current frame and the corresponding associated area;
for the state s (n) of the current frame, accumulating the amplitude according to the determined size of the associated area, and recording the state corresponding to the maximum amplitude accumulation value in the associated area
And selecting the distance resolution unit with the maximum amplitude of the previous frame in the association area of the current frame as the position of the target of the current frame, recording the position of the distance unit, and adding the amplitude of the distance unit to the amplitude of the distance unit corresponding to the previous frame. For example, the distance unit with the maximum amplitude of the object in the previous frame in the distance unit 178 corresponding to the associated area of the current frame is 179, the amplitude of the 179 th distance unit of the current accumulation period is added to the amplitude of the object in the 178 th distance unit of the previous frame, and the position of the object represented by the 179 th distance unit of the current frame is recorded.
S5, extracting a target peak value, specifically: when the Nth frame is accumulated, performing peak value extraction on the amplitude accumulation result to obtain an amplitude recursion accumulation result of the target; since the number of accumulation periods obtained during actual measurement is not large, amplitude recursive accumulation is performed on all periods during amplitude accumulation. And performing peak value extraction on the amplitude accumulation result to obtain an amplitude recursion accumulation result of the target. N is generally set to 20 to 25, and accumulation detection may be performed every 20 frames for data having a large accumulation period, and the process may be restarted from S2 at the time of the next accumulation detection.
S6, tracing trace points;
from the extraction result in step S5, the positions of the range units of the targets in all the accumulated frames recorded in step S4 are traced back, and the actual positions of the targets corresponding to the range units are calculated, thereby completing the positioning. The measured data of the invention is measured by a millimeter wave radar, and the obtained echo signal is processed by MATLAB. The positioning results obtained by using the traditional constant false alarm rate method are shown in fig. 5 and fig. 6, and the positioning results obtained by using the TBD method of the present invention are shown in fig. 7, so that the method of the present invention can effectively suppress false targets, and the positioning errors are shown in fig. 8.
When N is N-1, N-2, …,1, trace back according to the following equation:
the obtained trace point is estimated as
S7 point trace smoothing filtering
In order to make the trace of dots smoother, kalman filtering is performed on the trace of dots obtained in step S6, the smoothed trace of dots is shown in fig. 9, the error after filtering is shown in fig. 10, and the positioning result obtained by directly using the TBD method is shown, because of the existence of the error, there is diffusion on the theoretical path, and after the kalman filtering smoothing, the obtained trace of dots is more fitted with the theoretical path, so that the diffusion phenomenon is reduced, and therefore the result shown in fig. 9 is more consistent with the theoretical path than the result shown in fig. 7; comparing the error results before and after smoothing filtering can show that the point trace obtained after smoothing is closer to the theoretical path, namely the result precision is higher after smoothing processing.
Since the actual position of the target at each time cannot be accurately measured because the target is continuously moved during the actual measurement, when the positioning error is calculated, the positioning result is shifted from the theoretical path distance as shown in fig. 8 and 10 in the present embodiment,
when the target at the non-direct-view corner is positioned by adopting the TBD method, the target is detected by combining a plurality of accumulation periods, so that the signal-to-noise ratio of the target echo is greatly improved, and the detection probability and the positioning precision of the target are improved. According to the actual measurement result, the method can effectively position the target in the non-direct-view corner scene, can not cause false alarm and missing detection, and is correct and effective through verification.
It will be appreciated by those of ordinary skill in the art that the embodiments described herein are intended to assist the reader in understanding the principles of the invention and are to be construed as being without limitation to such specifically recited embodiments and examples. Various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (5)
1. A non-direct-view corner human body target positioning method based on TBD is characterized by comprising the following steps:
s1, pulse compression and incoherent accumulation are carried out on the collected radar echo data under the non-direct-view corner scene;
s2, setting initial values, specifically: setting the initial state as position information in two-dimensional directions of an x axis and a y axis, and taking the amplitude value of the first frame of observation data as an amplitude accumulation value of the first frame;
s3, determining the corresponding associated area of each frame;
s4, amplitude recursive accumulation, specifically: accumulating the amplitude according to the state of the current frame and the corresponding associated area;
s5, extracting a target peak value, specifically: when the Nth frame is accumulated, performing peak value extraction on the amplitude accumulation result to obtain an amplitude recursion accumulation result of the target;
s6, tracing trace points, specifically: according to the peak value extracted in the step S5, the positions of the distance units where the targets are located in all the accumulated frames in the step S4 are traced back, the real positions of the targets corresponding to the distance units are calculated, and target point trace estimation is obtained;
and S7, performing smoothing filtering on the target point trace estimation obtained in the step S6 to obtain a smoothed target point trace.
2. The method for positioning the non-direct-view corner human body target according to claim 1, wherein the step S3 is specifically as follows: and determining a possible area of the next frame target according to the distance unit of the previous frame target, wherein the area is the relevant area corresponding to the next frame.
3. The TBD-based non-direct-view corner human body target positioning method according to claim 2, is characterized in that the correlation area is determined by the motion speed of a target and a radar inter-frame sampling interval.
4. The TBD-based non-direct-view corner human body target positioning method according to claim 3, wherein the associated area corresponding to the next frame is an area formed by a distance unit where the target of the previous frame is located and a distance unit before and after the distance unit.
5. The TBD-based non-direct-view corner human body target positioning method according to any one of claims 2 to 4, wherein the step S4 is specifically as follows:
a1, taking the distance unit with the maximum amplitude of the previous frame in the association area of the current frame as the position of the target in the current frame;
and A2, adding the amplitude of the distance unit where the target is located determined in A1 and the amplitude of the distance unit where the target is located in the previous frame, and recording the distance unit where the target of the current frame is located.
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