阅读说明：本技术 基于雷达监测的地下停车场车辆跟踪方法及装置 (Underground parking lot vehicle tracking method and device based on radar monitoring ) 是由 胡友德 钱怡恬 刘钢 于 2019-10-28 设计创作，主要内容包括：本发明公开了基于雷达监测的地下停车场跟踪方法,雷达为毫米波雷达,方法包括以下步骤：S1：通过雷达的天线实时监测车辆,得到车辆的轨迹数据点,然后将所述轨迹数据点传输给处理模块；S2：处理模块从轨迹数据点中提取出多个参数；多个参数包括轨迹数据点的x坐标、y坐标、x方向速度、y方向速度、幅值、多普勒系数、时间单位和比例因子；S3：对同一时刻下的同一车辆,根据所述提取出的多个参数采用车辆的质心作为表示车辆在当前时刻下位置的坐标点；S4：将同一车辆的质心在地图上进行实时显示。本发明还公开了相应的跟踪装置。本发明能够准确地基于时间进行质心的跟踪,在现有质心轨迹的基础上进行下一时刻质心轨迹的预判。(The invention discloses an underground parking lot tracking method based on radar monitoring, wherein the radar is a millimeter wave radar, and the method comprises the following steps of S1, monitoring a vehicle in real time through an antenna of the radar to obtain a track data point of the vehicle, transmitting the track data point to a processing module, S2, extracting a plurality of parameters from the track data point by the processing module, wherein the parameters comprise an x coordinate, a y coordinate, an x-direction speed, a y-direction speed, an amplitude value, a Doppler coefficient, a time unit and a scale factor of the track data point, S3, regarding the same vehicle at the same time of , adopting the centroid of the vehicle as a coordinate point representing the position of the vehicle at the current time according to the extracted parameters, and S4, displaying the centroid of the same vehicle on a map in real time.)

1. The underground parking lot vehicle tracking method based on radar monitoring is characterized by comprising the following steps: the radar is a millimeter wave radar, and the method comprises the following steps:

s1: monitoring the vehicle in real time through an antenna of the radar to obtain a track data point of the vehicle, and then transmitting the track data point to a processing module;

s2: the processing module extracts a plurality of parameters from the trajectory data points; the plurality of parameters include an x coordinate, a y coordinate, an x-direction velocity, a y-direction velocity, an amplitude, a Doppler coefficient, a time unit, and a scale factor of the trajectory data point;

s3, adopting the center of mass of the vehicle as a coordinate point representing the position of the vehicle at the current time according to the extracted parameters for the vehicles at the same time ;

and S4, displaying the centroid of the vehicle on a map in real time.

2. An underground parking lot vehicle tracking method based on radar monitoring according to claim 1, characterized in that: in step S3, the process of using the centroid as the coordinate point representing the position of the vehicle at the current time according to the extracted parameters includes the following steps:

s31: removing static noise points and dynamic noise points of the vehicle at the current moment in the extracted multiple parameters to obtain data points after noise removal;

s32, obtaining the centroid and the effective data point range predicted at the current moment according to the vehicle motion trail, the centroid at the front moment and the speed parameters;

s33: and obtaining a coordinate point of the position at the current time according to the data point after the noise is removed, the centroid predicted at the current time and the effective data point range.

3. The method for tracking vehicles in underground parking lots based on radar monitoring as claimed in claim 2, wherein the step S32 of obtaining the predicted centroid and valid data point range at the current time according to the vehicle motion trail, the centroid and speed parameters at the previous time comprises the following steps:

s321, making a tangent line to the centroid at the front moment according to the motion track of the vehicle at the front moment, wherein the centroid predicted at the current moment is in the direction of the tangent line;

s322, in the tangential direction, increasing 5% of the centroid movement speed at the front moment to serve as a speed maximum value, decreasing 5% of the centroid movement speed at the front moment to serve as a speed minimum value, determining the diameter according to the speed maximum value, the speed minimum value and the time interval between the front moment and the current moment, wherein the middle point of the diameter is the centroid predicted at the current moment, and the circle formed by the diameter is the effective data point range.

4. An underground parking lot vehicle tracking method based on radar monitoring as claimed in claim 2, wherein: in step S33, the process of obtaining the coordinate point of the position at the current time according to the data point from which the noise is removed, the centroid predicted at the current time, and the valid data point range includes the following steps:

s331: obtaining a valid data point after the noise is removed according to the data point after the noise is removed and the valid data point range;

s332: and calculating a weight coefficient according to the distance between the effective data point after the noise is removed and the centroid predicted at the current moment, and obtaining a coordinate point of the position at the current moment according to the weight coefficient.

5. The method of claim 4The underground parking lot vehicle tracking method based on radar monitoring is characterized by comprising the following steps: in step S332, the coordinate point of the current position at the current time is

wherein d is_kRepresenting the distance from the k-th noise-removed data point of the vehicle to the center of the circle, d_lRepresenting the distance from the ith noise-removed valid data point of the vehicle to the center of the circle, d_mAnd the circle center is obtained by taking the tangential direction of the current moment centroid as the possible motion direction of the lower moment centroid, increasing the motion speed of the current moment centroid by 5% as the maximum speed value and decreasing by 5% as the minimum speed value, determining the diameter according to the maximum speed value, the minimum speed value and the time interval between the current moment and the lower moment, and drawing a circle by taking the midpoint of the diameter as the circle center, wherein the circle center is the midpoint of the diameter.

6. An underground parking lot vehicle tracking method based on radar monitoring as claimed in claim 2, wherein: in step S31, the process of removing the vehicle stationary noise point at the current time from the extracted plurality of parameters includes the steps of:

s311: and removing the static noise points with the Doppler coefficients being zero in the extracted multiple parameters.

7. An underground parking lot vehicle tracking method based on radar monitoring according to claim 1, characterized in that: in step S2, the process of extracting a plurality of parameters from the trajectory data point by the processing module includes the following steps:

s21: when a plurality of radars monitor the vehicle, a plurality of parameters are extracted from the track data points monitored by the radars together, and the rest track data points are dynamic noise points and are not extracted.

8. Underground parking garage vehicle tracking device based on radar monitoring, its characterized in that: the radar is a millimeter wave radar, the apparatus comprising:

a trace point data acquisition module: the radar system is used for monitoring the vehicle in real time through an antenna of the radar to obtain a track data point of the vehicle, and then transmitting the track data point to the processing module;

the processing module is used for extracting a plurality of parameters from the track data points, wherein the parameters comprise an x coordinate, a y coordinate, an x-direction speed, a y-direction speed, an amplitude value, a Doppler coefficient, a time unit and a scale factor of the track data points;

and the display module is used for displaying the centroid of the vehicle on a map in real time.

9. An underground parking lot vehicle tracking device based on radar monitoring as claimed in claim 8, wherein: the process of adopting the center of mass as a coordinate point for representing the position of the vehicle at the current moment according to the extracted parameters comprises the following steps:

1) removing static noise points and dynamic noise points of the vehicle at the current moment in the extracted multiple parameters to obtain data points after noise removal;

2) obtaining a centroid predicted at the current moment and an effective data point range according to the vehicle motion track, the centroid at the previous moment and the speed parameters;

3) and obtaining a coordinate point of the position at the current time according to the data point after the noise is removed, the centroid predicted at the current time and the effective data point range.

10. The radar-monitoring-based underground parking lot vehicle tracking device as recited in claim 9, wherein the process of obtaining the predicted centroid at the current moment and the valid data point range according to the vehicle motion track, the centroid at the previous moment and the speed parameters comprises:

1) tangent to the centroid at the front moment according to the vehicle motion trajectory at the front moment, the predicted centroid at the current moment being in the direction of the tangent;

2) in the tangential direction, the mass center movement speed at the front moment is increased by 5% to serve as a speed maximum value, the mass center movement speed at the front moment is decreased by 5% to serve as a speed minimum value, the diameter is determined according to the speed maximum value, the speed minimum value and the time interval between the front moment and the current moment, the diameter midpoint is the mass center predicted at the current moment, and a circle formed by the diameter is an effective data point range.

Technical Field

The invention relates to the field of radar, in particular to an underground parking lot vehicle tracking method and device based on radar monitoring.

Background

Disclosure of Invention

The invention aims to provide underground parking lot vehicle tracking methods and devices based on radar monitoring, which can solve the technical problems that in the prior art, the point trace processing is lagged, data acquisition has errors, only all parameters of a point trace at moments can be processed, and the point trace cannot be judged and tracked in continuous time.

The technical scheme is as follows: the invention relates to an underground parking lot vehicle tracking method based on radar monitoring, wherein the radar is a millimeter wave radar, and the method comprises the following steps:

s1: monitoring the vehicle in real time through an antenna of the radar to obtain a track data point of the vehicle, and then transmitting the track data point to a processing module;

s2: the processing module extracts a plurality of parameters from the trajectory data points; the plurality of parameters include an x coordinate, a y coordinate, an x-direction velocity, a y-direction velocity, an amplitude, a Doppler coefficient, a time unit, and a scale factor of the trajectory data point;

s3, adopting the center of mass of the vehicle as a coordinate point representing the position of the vehicle at the current time according to the extracted parameters for the vehicles at the same time ;

and S4, displaying the centroid of the vehicle on a map in real time.

, the step S3 of adopting the centroid as the coordinate point representing the position of the vehicle at the current time according to the extracted parameters comprises the following steps:

s31: removing static noise points and dynamic noise points of the vehicle at the current moment in the extracted multiple parameters to obtain data points after noise removal;

s32, obtaining the centroid and the effective data point range predicted at the current moment according to the vehicle motion trail, the centroid at the front moment and the speed parameters;

s33: and obtaining a coordinate point of the position at the current time according to the data point after the noise is removed, the centroid predicted at the current time and the effective data point range.

, in step S32, the process of obtaining the predicted centroid and the valid data point range at the current time according to the vehicle motion trajectory, the centroid at the previous time and the speed parameters includes the following steps:

s321, making a tangent line to the centroid at the front moment according to the motion track of the vehicle at the front moment, wherein the centroid predicted at the current moment is in the direction of the tangent line;

s322, in the tangential direction, increasing 5% of the centroid movement speed at the front moment to serve as a speed maximum value, decreasing 5% of the centroid movement speed at the front moment to serve as a speed minimum value, determining the diameter according to the speed maximum value, the speed minimum value and the time interval between the front moment and the current moment, wherein the middle point of the diameter is the centroid predicted at the current moment, and the circle formed by the diameter is the effective data point range.

, in step S33, the process of obtaining the coordinate point of the position at the current time according to the data point after removing the noise, the centroid predicted at the current time, and the valid data point range includes the following steps:

s331: obtaining a valid data point after the noise is removed according to the data point after the noise is removed and the valid data point range;

s332: and calculating a weight coefficient according to the distance between the effective data point after the noise is removed and the centroid predicted at the current moment, and obtaining a coordinate point of the position at the current moment according to the weight coefficient.

, in the step S332, the coordinate point of the current position at the time is

Wherein x is_iAn abscissa representing an ith noise-removed data point of the vehicle, n representing a total number of trajectory data points of the vehicle,

denotes x_iThe weight of (a) is obtained by the formula (1); y is_iAn ordinate representing an ith trajectory data point of the vehicle,denotes y_iThe weight of (a) is obtained by the formula (2);

wherein d is_kRepresenting the distance from the k-th noise-removed data point of the vehicle to the center of the circle, d_lRepresenting the distance from the ith noise-removed valid data point of the vehicle to the center of the circle, d_mThe circle center is obtained by taking the tangential direction of the current time centroid as the possible motion direction of the lower time centroid, increasing the motion speed of the current time centroid by 5% as the maximum speed value and decreasing the motion speed by 5% as the minimum speed value, determining the diameter according to the maximum speed value, the minimum speed value and the time interval between the current time and the lower time, drawing a circle by taking the midpoint of the diameter as the circle center, wherein the circle center is the midpoint of the diameter.

, in the step S31, the process of removing the static noise point of the vehicle at the current time from the extracted parameters includes the following steps:

s311: and removing the static noise points with the Doppler coefficients being zero in the extracted multiple parameters.

, in step S2, the process of the processing module extracting a plurality of parameters from the trajectory data point includes the following steps:

and S21, when a plurality of radars monitor the vehicle, extracting a plurality of parameters from the track data points jointly detected by the radars, wherein the rest track data points are dynamic noise points and do not extract parameters from the dynamic noise points, and the weight of the centroid at each lower moment is influenced by the parameters at the current moment, so that the accuracy of the track can be continuously optimized by removing the dynamic noise points.

The invention relates to an underground parking lot vehicle tracking device based on radar monitoring, wherein the radar is a millimeter wave radar, and the device comprises:

a trace point data acquisition module: the radar system is used for monitoring the vehicle in real time through an antenna of the radar to obtain a track data point of the vehicle, and then transmitting the track data point to the processing module;

the processing module is used for extracting a plurality of parameters from the track data points, wherein the parameters comprise an x coordinate, a y coordinate, an x-direction speed, a y-direction speed, an amplitude value, a Doppler coefficient, a time unit and a scale factor of the track data points;

and the display module is used for displaying the centroid of the vehicle on a map in real time.

, the step of using the centroid as a coordinate point for representing the position of the vehicle at the current time according to the extracted parameters comprises:

1) removing static noise points and dynamic noise points of the vehicle at the current moment in the extracted multiple parameters to obtain data points after noise removal;

2) obtaining a centroid predicted at the current moment and an effective data point range according to the vehicle motion track, the centroid at the previous moment and the speed parameters;

3) and obtaining a coordinate point of the position at the current time according to the data point after the noise is removed, the centroid predicted at the current time and the effective data point range.

Step , the process of obtaining the predicted centroid and the valid data point range at the current time according to the vehicle motion trajectory, the centroid at the previous time and the speed parameters includes:

1) tangent to the centroid at the front moment according to the vehicle motion trajectory at the front moment, the predicted centroid at the current moment being in the direction of the tangent;

2) in the tangential direction, the mass center movement speed at the front moment is increased by 5% to serve as a speed maximum value, the mass center movement speed at the front moment is decreased by 5% to serve as a speed minimum value, the diameter is determined according to the speed maximum value, the speed minimum value and the time interval between the front moment and the current moment, the diameter midpoint is the mass center predicted at the current moment, and a circle formed by the diameter is an effective data point range.

The invention discloses underground parking lot vehicle tracking methods and devices based on radar monitoring, which adopt millimeter wave radar to monitor objects, are not influenced by environmental factors, and can stably acquire data under any environmental conditions, moreover, the invention transmits video data instead, has small data amount, can ensure high accuracy and low delay lag, thereby accurately tracking the centroid based on time, in addition, the invention can judge and track the centroid in continuous time, and can pre-judge the centroid track at the next moment on the basis of the existing centroid track.

Drawings

FIG. 1 is a flow chart of a method in accordance with an embodiment of the present invention;

FIG. 2 is a schematic diagram of a process for using a centroid as a coordinate point for characterizing the position of an object at that time in an embodiment of the present invention;

FIG. 3 is a schematic diagram of finding a centroid at different times in an embodiment of the present invention;

FIG. 4 is a trace of the centroid at different times in an embodiment of the present invention;

FIG. 5 is a schematic illustration of multiple radar monitoring in an embodiment of the present invention;

fig. 6 is a schematic diagram of a process of finding a centroid in an embodiment of the present invention.

Detailed Description

The specific embodiment discloses underground parking lot vehicle tracking methods based on radar monitoring, wherein the radar is a millimeter wave radar, and as shown in fig. 1, the method comprises the following steps:

s1: monitoring the vehicle in real time through an antenna of the radar to obtain a track data point of the vehicle, and then transmitting the track data point to a processing module;

s2, a processing module extracts a plurality of parameters from the track data points, wherein the parameters comprise an X coordinate, a Y coordinate, an X-direction speed, a Y-direction speed, an amplitude, a Doppler coefficient, a time unit and a scale factor of the track data points, and other related parameters can be obtained according to the parameters, such as the range of points obtained through calculation according to the X coordinate and the Y coordinate for judging distance, the points with the same time parameters are data in the same frames (the frames have computer clock periods of about 44.5ms), a plurality of trace data are arranged in the same frames, and each point is packaged into a point with parameters such as D (Doppler coefficient), P (amplitude), X (X coordinate), Y (Y coordinate), N ( number of points in the frames), XSIZE (X area size), YSIZE (Y area size), VX (X-direction speed size), VY (Y-direction speed size) and the like;

s3, adopting the center of mass of the vehicle as a coordinate point representing the position of the vehicle at the current time according to the extracted parameters for the same vehicle at the same time, as shown in FIG. 2;

and S4, displaying the centroid of the vehicle on a map in real time.

In step S3, the process of using the centroid as the coordinate point representing the position of the vehicle at the current time according to the extracted parameters includes the following steps:

s31: removing static noise points and dynamic noise points of the vehicle at the current moment in the extracted multiple parameters to obtain data points after noise removal;

s32, obtaining the centroid and the effective data point range predicted at the current moment according to the vehicle motion trail, the centroid at the front moment and the speed parameters;

s33: and obtaining a coordinate point of the position at the current time according to the data point after the noise is removed, the centroid predicted at the current time and the effective data point range.

In step S32, the process of obtaining the predicted centroid and valid data point range at the current time according to the vehicle motion trajectory, the centroid at the previous time, and the speed parameter includes the following steps:

s321, making a tangent line to the centroid at the front moment according to the motion track of the vehicle at the front moment, wherein the centroid predicted at the current moment is in the direction of the tangent line;

s322, in the tangential direction, increasing 5% of the centroid movement speed at the front moment to serve as a speed maximum value, decreasing 5% of the centroid movement speed at the front moment to serve as a speed minimum value, determining the diameter according to the speed maximum value, the speed minimum value and the time interval between the front moment and the current moment, wherein the middle point of the diameter is the centroid predicted at the current moment, and the circle formed by the diameter is the effective data point range.

In step S33, the process of obtaining the coordinate point of the position at the current time according to the data point from which the noise is removed, the centroid predicted at the current time, and the valid data point range includes the following steps:

s331: obtaining a valid data point after the noise is removed according to the data point after the noise is removed and the valid data point range;

s332: and calculating a weight coefficient according to the distance between the effective data point after the noise is removed and the centroid predicted at the current moment, and obtaining a coordinate point of the position at the current moment according to the weight coefficient.

In step S2, the plurality of parameters include an x coordinate, a y coordinate, an x-direction velocity, a y-direction velocity, a magnitude, a doppler coefficient, a time unit, and a scale factor of the point.

The millimeter wave radar can remove static noise and random noise by using the detected Doppler coefficient, so that the obtained centroid is more accurate, and in step S332, the coordinate point of the current position at the current time is

Wherein x is_iAn abscissa representing an ith noise-removed data point of the vehicle, n representing a total number of trajectory data points of the vehicle,

denotes x_iThe weight of (a) is obtained by the formula (1); y is_iAn ordinate representing an ith trajectory data point of the vehicle,

denotes y_iThe weight of (a) is obtained by the formula (2);

wherein d is_kRepresenting the distance from the k-th noise-removed data point of the vehicle to the center of the circle, d_lRepresenting the distance from the ith noise-removed valid data point of the vehicle to the center of the circle, d_mAnd the circle center is obtained by taking the tangential direction of the current moment centroid as the possible motion direction of the lower moment centroid, increasing the motion speed of the current moment centroid by 5% as the maximum speed value and decreasing by 5% as the minimum speed value, determining the diameter according to the maximum speed value, the minimum speed value and the time interval between the current moment and the lower moment, and drawing a circle by taking the midpoint of the diameter as the circle center, wherein the circle center is the midpoint of the diameter.

The centroid finding process is shown in fig. 6 and 3. Fig. 4 is a trace of the centroid at different times.

In step S31, the process of removing the static noise point of the vehicle at the current time from the extracted plurality of parameters includes the steps of:

s311: and removing the static noise points with the Doppler coefficients being zero in the extracted multiple parameters.

In step S2, the process of extracting a plurality of parameters from the trajectory data point by the processing module includes the following steps:

s21: when a plurality of radars monitor the vehicle, a plurality of parameters are extracted from the track data points jointly detected by the radars, and the rest track data points are dynamic noise points and are not used for extracting parameters.

This embodiment discloses underground parking garage vehicle tracking device based on radar monitoring, and the radar is the millimeter wave radar, and the device includes:

a trace point data acquisition module: the radar system is used for monitoring the vehicle in real time through an antenna of the radar to obtain a track data point of the vehicle, and then transmitting the track data point to the processing module;

the processing module is used for extracting a plurality of parameters from the track data points, wherein the parameters comprise an x coordinate, a y coordinate, an x-direction speed, a y-direction speed, an amplitude value, a Doppler coefficient, a time unit and a scale factor of the track data points;

and the display module is used for displaying the centroid of the vehicle on a map in real time.

The process that the mass center is adopted by the extracted parameters as a coordinate point for representing the position of the vehicle at the current time comprises the following steps:

1) removing static noise points and dynamic noise points of the vehicle at the current moment in the extracted multiple parameters to obtain data points after noise removal;

2) obtaining a centroid predicted at the current moment and an effective data point range according to the vehicle motion track, the centroid at the previous moment and the speed parameters;

3) and obtaining a coordinate point of the position at the current time according to the data point after the noise is removed, the centroid predicted at the current time and the effective data point range.

The process of obtaining the predicted centroid and the effective data point range at the current moment according to the motion trail of the vehicle, the centroid at the previous moment and the speed parameters comprises the following steps:

1) tangent to the centroid at the front moment according to the vehicle motion trajectory at the front moment, the predicted centroid at the current moment being in the direction of the tangent;

2) in the tangential direction, the mass center movement speed at the front moment is increased by 5% to serve as a speed maximum value, the mass center movement speed at the front moment is decreased by 5% to serve as a speed minimum value, the diameter is determined according to the speed maximum value, the speed minimum value and the time interval between the front moment and the current moment, the diameter midpoint is the mass center predicted at the current moment, and a circle formed by the diameter is an effective data point range.

The process of obtaining the coordinate point of the position at the current time according to the data point after the noise is removed, the centroid predicted at the current time and the effective data point range comprises the following steps:

1) obtaining a valid data point after the noise is removed according to the data point after the noise is removed and the valid data point range;

2) and calculating a weight coefficient according to the distance between the effective data point after the noise is removed and the centroid predicted at the current moment, and obtaining a coordinate point of the position at the current moment according to the weight coefficient.

The coordinate point of the position at the current time isWherein x is_iAn abscissa representing an ith noise-removed data point of the vehicle, n representing a total number of trajectory data points of the vehicle,denotes x_iThe weight of (a) is obtained by the formula (3); y is_iAn ordinate representing an ith trajectory data point of the vehicle,denotes y_iBy a weight ofFormula (4);

wherein d is_kRepresenting the distance from the k-th noise-removed data point of the vehicle to the center of the circle, d_lRepresenting the distance from the ith noise-removed valid data point of the vehicle to the center of the circle, d_mAnd the circle center is obtained by taking the tangential direction of the current moment centroid as the possible motion direction of the lower moment centroid, increasing the motion speed of the current moment centroid by 5% as the maximum speed value and decreasing by 5% as the minimum speed value, determining the diameter according to the maximum speed value, the minimum speed value and the time interval between the current moment and the lower moment, and drawing a circle by taking the midpoint of the diameter as the circle center, wherein the circle center is the midpoint of the diameter.

The process of removing the static noise point of the vehicle at the current moment in the extracted multiple parameters comprises the following steps: and removing the static noise points with the Doppler coefficients being zero in the extracted multiple parameters.

The process of extracting a plurality of parameters from the trajectory data point by the processing module comprises the following steps: when a plurality of radars monitor the vehicle, a plurality of parameters are extracted from the track data points jointly detected by the radars, and the rest track data points are dynamic noise points and are not used for extracting parameters.

In this embodiment, when multiple radars monitor the vehicle, multiple parameters are extracted from the trace data points detected by the multiple radars, and the rest of the trace data points are dynamic noise points, and no parameter is extracted from the dynamic noise points, because the weight of the centroid at each lower moment is affected by the parameters at the current moment, the removal of the dynamic noise points can continuously optimize the accuracy of the trace.