A method for estimating the household throwing objects from a height based on a parabolic model

Abstract

The present invention discloses a method for estimating the household where high-altitude objects are thrown based on a parabolic model. When the millimeter-wave radar system monitors high-altitude object throwing in real time, this method uses the parabolic model to estimate the position of the household where the object is thrown. According to the falling trajectories of some two-dimensional or three-dimensional targets that have been detected by the radar, this method combines the classical mechanics parabolic model for non-linear curve fitting, predicts and complements the actual parabolic motion trajectory, and then reversely deduces the position range of the household where the object is thrown, effectively improving the radar's ability to estimate and monitor high-altitude object throwing.

Description

Technical Field

[0001] The present invention relates to the fields of millimeter-wave radar detection and urban security, and particularly to a method for estimating the residents throwing objects from high altitude based on a parabolic model, which can effectively improve the ability of millimeter-wave radar to estimate and monitor objects thrown from high altitude. Background Art

[0002] Monitoring of objects thrown from high altitude is the key to preventing and deterring such behaviors. Relevant research has been carried out on this issue in both academic and industrial circles. Existing monitoring means for objects thrown from high altitude are implemented based on visual detection technology. However, the visual-dominated monitoring scheme for objects thrown from high altitude is extremely vulnerable to environmental factors. Its performance deteriorates severely in environments with reduced light (night) or extreme weather conditions (such as fog, sand and dust, etc.).

[0003] The basic principle of radar determines its natural advantage in monitoring moving targets. Millimeter-wave radar operates in the millimeter-wave (30 - 300 GHz) frequency band. Due to its small size, it can work all-weather and has extremely high spatial resolution. It has developed rapidly in recent years and is widely used in the detection of moving targets, showing great potential in detecting various types of objects thrown from high altitude. However, due to the short wavelength, low transmit power and limited coverage area of millimeter-wave radar, millimeter-wave radar often can only detect partial trajectories of objects thrown from high altitude and cannot accurately determine the residents on higher floors who throw objects. Although some scholars have proposed millimeter-wave radar systems for detecting objects thrown from high altitude (such as the technology disclosed in Chinese Patent Application Publication No. CN110082751A), and methods for judging whether there is an act of throwing objects from high altitude by fitting object trajectories (such as the technology disclosed in Chinese Patent Application Publication No. CN111553256A), there is no method for improving the ability of millimeter-wave radar to estimate and monitor objects thrown from high altitude by using the trajectories of objects thrown from high altitude.

[0004] Therefore, there is an urgent need to propose a method for estimating the residents throwing objects from high altitude. Summary of the Invention

[0005] In view of the deficiency that the existing millimeter-wave radar has a limited coverage area for objects thrown from high altitude, the present invention provides a method for estimating the residents throwing objects from high altitude based on a parabolic model.

[0006] To achieve the above invention object, the technical solution of the present invention is: A method for estimating the residents throwing objects from high altitude based on a parabolic model, including the following specific steps:

[0007] Collect and continuously process multiple frames of millimeter-wave radar echo complex signals, and use the angle-of-arrival estimation method to calculate the spatial azimuth angle of the moving target in each frame of signal, so as to obtain the two-dimensional or three-dimensional motion trajectory of the moving target;

[0008] According to the detected two-dimensional or three-dimensional parabolic motion trajectory, fit it with a parabolic model to complete the two-dimensional or three-dimensional motion trajectory of the moving target, calculate the parabolic height, and obtain the position range of the household throwing objects from a high altitude.

[0009] Further, a period of the transmitted signal of the millimeter-wave radar is a frame period, and the frame period includes several pulses or continuous wave modulation signals; the frame period is less than 50 us.

[0010] Further, a frame of radar echo range-Doppler response diagram is obtained by processing the echo signal within one frame period; the background clutter interference is removed from the radar echo range-Doppler response diagram through a finite impulse response high-pass filter, and the range information of the moving target to the radar is detected using a constant false alarm rate algorithm.

[0011] Further, by combining the spatial azimuth angle of the moving target and the range of the moving target to the radar within each frame of signal, the position of the moving target within each frame of signal is obtained, and the positions of the moving target within all signal frames are superimposed to obtain the two-dimensional or three-dimensional motion trajectory of the moving target.

[0012] Further, the target two-dimensional or three-dimensional motion trajectory is related to the number of transceiver channels of the millimeter-wave radar and the type of transceiver combined antenna array; if the transceiver combined antenna array is linearly arranged, only the azimuth angle of the moving target in the two-dimensional plane is analyzed to obtain the two-dimensional motion trajectory; if the transceiver combined antenna array is arranged in a plane, the azimuth angle of the moving target in space is analyzed to obtain the three-dimensional motion trajectory in space.

[0013] Further, the angle-of-arrival estimation methods include beamforming method, minimum variance distortionless response beam scanning method, and multiple signal classification method.

[0014] Further, an object cannot be regarded as an ideal particle. When there is a high-altitude object-throwing target, several discrete target points will be added to the RD diagram of the latter frame compared with the previous frame. It is necessary to perform clustering processing on all detected target points, judge the range and velocity information of the high-altitude object-throwing target and record it; when the number of discrete target points is small and the complexity is low, direct clustering processing is used to judge the range and velocity of the target points to the radar, and the angle-of-arrival information of multiple frames of targets is analyzed to obtain the motion trajectory of the moving target.

[0015] Further, the parabolic model has the following differential equation form, and the air resistance is linearly related to the velocity:

[0016]

[0017]

[0018] is the object motion velocity is the coordinate of the object's movement, is the acceleration due to gravity, and α is the drag coefficient;

[0019] Furthermore, based on the parabolic model, the nonlinear least squares method is used to fit the two-dimensional or three-dimensional movement trajectory of the moving target. By adjusting the time point t = t0 of the first detected target point in all signal frames within a set range during the entire parabolic process, and adjusting the drag parameter α of the parabolic model at each time point for fitting, the fitting movement trajectory with the minimum mean square error of the fitting between the fitting movement trajectory and the actual movement trajectory is used as the optimal fitting parabolic trajectory. The formula is as follows:

[0020]

[0021] where, is the coordinate of the i-th detected point in the actual detection trajectory, is the coordinate of the i-th fitting point in the fitting trajectory, and n is the number of detected points in the actual movement trajectory.

[0022] Furthermore, for the predicted trajectory of the high-altitude parabolic target obtained by fitting, according to the obtained optimal time point when the first target appears, the horizontal and vertical positions of the parabolic target at the initial time of the entire parabolic process are determined, so as to predict and judge the position of the parabolic household. The beneficial effects of the present invention are as follows: The method of the present invention can perform nonlinear curve fitting by combining the classical mechanics parabolic model with the detected partial two-dimensional or three-dimensional target falling trajectories of the radar, predict and complete the actual parabolic movement trajectory, and then deduce the position range of the parabolic household, effectively improving the radar's ability to estimate and monitor high-altitude parabolic objects. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a schematic flow chart of a method for estimating high-altitude parabolic households based on a parabolic model;

[0024] Figure 2 is a comparison of the RD maps of two frames before and after detecting the first abnormal target in a specific embodiment of the inventive method;

[0025] Figure 3 is the detected point of the two-dimensional trajectory of the moving target in a specific embodiment of the inventive method;

[0026] Figure 4 is a graph of the fitting of the two-dimensional trajectory of the moving target and the prediction of the parabolic position in a specific embodiment of the inventive method. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] The following will further illustrate the technical methods in the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Based on the embodiments in the present invention, for those of ordinary skill in the art, other embodiments obtained without creative efforts fall within the protection scope of the present invention.

[0028] An embodiment of the present invention is as Figure 1 shown. The present invention proposes a method for estimating the residents who throw objects from high altitude based on a parabolic model, and the specific steps are as follows:

[0029] (1) Install a millimeter-wave radar in the monitoring area of high-rise buildings;

[0030] Furthermore, the millimeter-wave radar system is installed on the ground near the north and south sides of the building. The detection beam direction of the radar antenna is vertically upward, and the arrangement direction of the linear antenna array is parallel to the plane of the building wall.

[0031] Exemplarily preferably, the millimeter-wave radar system adopts a three-transmit and four-receive linear microstrip antenna array. Specifically, the transmitted signal of the millimeter-wave radar system is a frequency-modulated continuous wave signal. The frequency-modulated continuous wave (FMCW) signal uses a 77GHz frequency band.

[0032] (2) Processing of the monotonic frequency-period radar echo signal: The millimeter-wave radar transmits a signal to monitor the suspicious object-throwing area of the high-rise building, demodulates the radar echo, and records it by real-time digital sampling to obtain the original sampling data of the radar echo.

[0033] (3) Processing of the multi-frequency-period radar echo signal: The millimeter-wave radar samples the original complex signal within multiple pulse periods or continuous wave periods, and through two fast Fourier transforms, obtains a radar echo range-Doppler response diagram (RD diagram) containing background clutter; applies a finite impulse response (FIR) high-pass filter to filter the background clutter interference near zero Doppler, and uses the constant false alarm rate (CFAR) algorithm to detect the range and velocity information of moving targets.

[0034] Specifically, the CFAR detection algorithm can adopt algorithms such as the cell averaging method (CA-CFAR), the cell maximum method (GO-CFAR), and the ordered statistics method (OS-CFAR). Exemplarily preferably, the CA-CFAR algorithm is used for target detection.

[0035] One period of the transmitted signal of the millimeter-wave radar is the frame period, and the one frame period includes a number of pulse or continuous wave modulation signals. An image obtained by processing the echo signal within one frame period. Furthermore, the setting of the frame period should be less than 50us to ensure that there is no velocity ambiguity in detecting moving targets.

[0036] Furthermore, a moving object cannot be regarded as an ideal particle. When there is a high-altitude parabolic target, several discrete target points will be added to the RD map of the latter frame compared with the previous frame. It is necessary to cluster all the detected target points to judge the distance and speed information of the high-altitude parabolic target and record it. When the number of discrete target points is small and the complexity is low, direct clustering processing is used to judge the distance and speed of the target points from the radar, and the arrival angle information of multiple-frame targets is analyzed for subsequent obtaining of the motion trajectory of the moving target.

[0037] Furthermore, by comparing the detection results of the RD maps obtained from the processing of two consecutive frames, if an abnormal target is detected, its distance and speed information will be recorded. Exemplarily, Figure 2 This is a comparison diagram of the RD maps of the front and rear frames when the radar in this embodiment detects an abnormal target. By comparing the RD maps obtained from the clutter suppression processing of two consecutive frames, an abnormal moving target (circled by a rectangular frame) appears in the latter frame (the 84th frame), and its distance and speed information is recorded by the radar system. In addition to the abnormal moving target circled by the rectangular frame in the 84th frame, there are many unfiltered background interference points (i.e., the white points in the figure) near the dotted line with a speed of 0. And in several consecutive frames after the 84th frame, these white points do not change significantly, and these points are determined as background interference points. Therefore, although Figure 2 the detection points in the rest of the two frames change slightly, they are determined as background noise echoes by the clutter suppression method and are not recorded as abnormal targets.

[0038] (4) Signal target space trajectory detection: Continuously process the radar echo complex signals of multiple frames. When there is a high-altitude parabolic target, it is further analyzed and processed using the arrival angle estimation method to calculate the spatial azimuth angle of the moving target in each frame of the signal. Combining with the distance information of the target obtained in step (3), the position of the moving target in each frame of the signal is obtained, and the positions of the moving targets in all signal frames are superimposed to obtain the two-dimensional motion trajectory of the moving target in the plane parallel to the building wall or the three-dimensional motion trajectory in space.

[0039] Furthermore, algorithms such as beamforming (BF), minimum variance distortionless response beam scanning method (Capon), and multiple signal classification method (MUSIC) can be used for the arrival angle estimation method of the target. Exemplarily preferably, the Capon method is used for arrival angle estimation.

[0040] The two-dimensional or three-dimensional motion trajectory of the target is related to the number of transceiver channels of the millimeter-wave radar and the type of transceiver combined antenna array; if the transceiver combined antenna array is linearly arranged, only the azimuth angle of the moving target in the two-dimensional plane is analyzed to obtain the two-dimensional motion trajectory; if the transceiver combined antenna array is arranged in a plane, the azimuth angle of the moving target in space is analyzed to obtain the three-dimensional motion trajectory in space.

[0041] Specifically, referring to Figure 3 in this embodiment, the millimeter-wave radar synthetic antenna array is linearly arranged parallel to the plane of the building wall, and the obtained motion trajectory is the two-dimensional motion trajectory of the moving target within the plane parallel to the building wall surface.

[0042] (5) Using the parabolic model for predicting the parabolic household: Combining the principles of classical mechanics, according to the detected two-dimensional or three-dimensional motion trajectory in step (4), use the method of curve fitting to analyze a suitable classical mechanics falling object model, and estimate the air resistance coefficients in the vertical and horizontal directions of the falling object. Based on the air resistance coefficients of the fitting model, complete the actual parabolic trajectory, and then predict the position range of the actual high-altitude parabolic household.

[0043] Specifically, the parabolic model is established based on classical mechanics theory and has the following differential equation form, where the air resistance is linearly related to the velocity.

[0044]

[0045] is the velocity of the object's motion, is the coordinate of the object's motion, is the acceleration due to gravity, and α is the resistance coefficient.

[0046] Furthermore, based on the parabolic model, the non-linear least squares method is used to fit the detected two-dimensional motion trajectory. By adjusting the time point t = t0 of the first detected target point in all signal frames within the set range during the entire parabolic process, and adjusting the resistance parameter α of the parabolic model at each time point for fitting processing, the optimal fitting model is obtained.

[0047] Furthermore, under the optimal fitting model, the mean square error of the fit between the fitting trajectory and the actual motion trajectory is the smallest, that is is the coordinate of the i-th detected point in the actual detected trajectory, is the coordinate of the i-th fitting point in the fitting trajectory, and n is the number of detected points of the actual motion trajectory.

[0048] Furthermore, for the predicted trajectory of the high-altitude parabolic target obtained by fitting, the horizontal and vertical positions of the target at the initial time of the entire parabola (i.e., time t = 0) can be determined according to the obtained optimal time point when the first target appears, so as to predict and judge the position of the parabolic household.

[0049] Exemplarily, in the embodiment of the present invention, the adjustment range of the time point t0 when the first target appears is selected to be from 0 to 1 second, and the adjustment step is 0.1 second. As Figure 4As shown in the prediction results, the optimal time point t0 when the first detection target appears is determined to be 0.5 seconds, the actual number of trajectory points obtained by fitting is 107, the optimal drag coefficient α is 1.196, the minimum mean square error is 0.52 m, the horizontal position is -3.05 meters, and the vertical position is 18.52 meters. Calculated according to the floor height of the test building being 3.5 meters, the household where the object was thrown is about the household on the 5th floor.

[0050] In summary, through the comparison of radar detection RD maps of consecutive frames and in combination with clutter suppression methods, the present invention maximally suppresses the false target points caused by background noise and improves the anti-interference ability of millimeter-wave radar in detecting high-altitude parabolic objects. The present invention combines the classical mechanics parabolic model to correct and complete the high-altitude parabolic trajectories detected by the existing millimeter-wave radar, so as to predict the actual position of the household where the high-altitude object is thrown, effectively improving the ability of the millimeter-wave radar to estimate and monitor high-altitude parabolic objects.

[0051] The above embodiments are only used to illustrate the design concept and characteristics of the present invention, and the purpose is to enable those skilled in the art to understand the content of the present invention and implement it accordingly. The protection scope of the present invention is not limited to the above embodiments. Therefore, all equivalent changes or modifications made based on the principles and design ideas disclosed by the present invention are within the protection scope of the present invention.

Claims

1. A method for estimating the household of high-altitude parabolic objects based on a parabolic model, characterized in that, It includes the following specific steps: Collect and continuously process multi-frame millimeter-wave radar echo complex signals, use the angle-of-arrival estimation method to calculate the spatial azimuth angle of moving targets in each frame of signal, and obtain the two-dimensional or three-dimensional motion trajectory of the moving targets; According to the detected parabolic two-dimensional or three-dimensional motion trajectory, fit it with the parabolic model, complete the two-dimensional or three-dimensional motion trajectory of the moving target, calculate the parabolic height, and obtain the position range of the household where the high-altitude parabolic occurs; Including: according to the parabolic model, using the nonlinear least squares method to fit with the two-dimensional or three-dimensional motion trajectory of the moving target, and adjusting the time point of the first detected target point in all signal frames during the entire parabolic process within a set range , and adjusting the drag parameter of the parabolic model at each time point to perform the fitting process, and taking the fitting motion trajectory with the minimum mean square error of the fitting between the fitting motion trajectory and the actual motion trajectory as the optimal fitting parabolic trajectory. The formula is as follows: ； Among them, is the coordinate of the i-th detection point in the actual detection trajectory, is the coordinate of the i-th fitting point in the fitting trajectory, and n is the number of detection points of the actual motion trajectory; For the predicted trajectory of the high-altitude parabolic target obtained by fitting, according to the obtained optimal time point when the first target appears, determine the horizontal and vertical positions of the parabolic target at the initial time of the entire parabolic process, so as to predict and judge the position of the household where the parabolic occurs.

2. The method for estimating the household throwing objects from high altitude based on the parabolic model according to claim 1, wherein One period of the transmitted signal of the millimeter-wave radar is one frame period, and the one frame period includes several pulses or continuous wave modulation signals; the frame period is less than 50 us.

3. The method for estimating the household throwing objects from a height based on the parabolic model according to claim 2, wherein A frame of radar echo range-Doppler response map obtained by processing the echo signal within one frame period; remove the background clutter interference from the radar echo range-Doppler response map through a finite impulse response high-pass filter, and use the constant false alarm rate algorithm to detect the distance information of the moving target to the radar.

4. The method for estimating the household throwing objects from a height based on a parabolic model according to claim 1 or 3, characterized in that, By combining the spatial azimuth angle of the moving target and the distance from the moving target to the radar within each frame of signal, obtain the position of the moving target within each frame of signal, and superimpose the positions of the moving target in all signal frames to obtain the two-dimensional or three-dimensional motion trajectory of the moving target.

5. The method for estimating the household throwing objects from a height based on the parabolic model according to claim 1, wherein The two-dimensional or three-dimensional motion trajectory of the target is related to the number of transceiver channels of the millimeter-wave radar and the type of transceiver combined antenna array; if the transceiver combined antenna array is linearly arranged, only analyze the azimuth angle of the moving target in the two-dimensional plane to obtain the two-dimensional motion trajectory; if the transceiver combined antenna array is arranged in a plane, analyze and obtain the azimuth angle of the moving target in space to obtain the three-dimensional motion trajectory in space.

6. The method for estimating the household throwing objects from high altitude based on the parabolic model according to claim 1, wherein The angle-of-arrival estimation methods include beamforming method, minimum variance distortionless response beam scanning method, and multiple signal classification method.

7. The method for estimating the household throwing objects from high altitude based on the parabolic model according to claim 1, characterized in that, An object cannot be regarded as an ideal particle. When there is a high-altitude parabolic target, several discrete target points will be added to the RD map of the latter frame compared with the previous frame. It is necessary to perform clustering processing on all detected target points, judge the distance and speed information of the high-altitude parabolic target and record it; when the number of discrete target points is small and the complexity is low, use direct clustering processing to judge the distance and speed of the target points to the radar, and analyze the angle-of-arrival information of multiple frames of targets to obtain the motion trajectory of the moving target.

8. The method for estimating the household throwing objects from a height based on a parabolic model according to claim 1, wherein The parabolic model has the following differential equation form, and the air resistance is linearly related to the velocity: ； In the formula, is the velocity of the object's motion, is the coordinate of the object's motion, is the acceleration due to gravity, is the drag coefficient, and t is the time.

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