阅读说明：本技术 一种基于椭圆霍夫变换的目标跟踪方法和系统 (Target tracking method and system based on ellipse Hough transform ) 是由 饶彬 周永坤 蔡桂权 王伟 王涛 周颖 邹小海 徐峰 于 2021-01-22 设计创作，主要内容包括：本发明公开了一种基于椭圆霍夫变换的目标跟踪方法和系统,方法包括以下步骤：获取雷达站的第一量测数据；将第一量测数据转换为预设坐标系下的第二量测数据；预设坐标系下具有预设椭圆方程,预设椭圆方程具有目标参数；根据预设量化参数、预设椭圆方程以及第二量测数据,确定检测点数据；根据检测点数据,确定目标的跟踪轨迹。本发明通过将获取的雷达站的第一量测数据转换为预设坐标系下的第二量测数据进行处理,并结合符合弹道目标轨迹的预设椭圆方程,根据预设椭圆方程、预设量化参数以及第二量测数据,确定检测点数据从而确定目标的跟踪轨迹,能够对弹道目标进行检测跟踪。本发明可广泛应用于雷达技术领域。(The invention discloses a target tracking method and a target tracking system based on ellipse Hough transform, wherein the method comprises the following steps of: acquiring first measurement data of a radar station; converting the first measurement data into second measurement data under a preset coordinate system; a preset elliptic equation is arranged under a preset coordinate system, and the preset elliptic equation has target parameters; determining detection point data according to a preset quantization parameter, a preset ellipse equation and second measurement data; and determining the tracking track of the target according to the detection point data. According to the method, the acquired first measurement data of the radar station are converted into second measurement data under a preset coordinate system to be processed, the preset elliptic equation which accords with the trajectory of the ballistic target is combined, and the detection point data are determined according to the preset elliptic equation, the preset quantitative parameters and the second measurement data, so that the tracking trajectory of the target is determined, and the ballistic target can be detected and tracked. The invention can be widely applied to the technical field of radars.)

1. A target tracking method based on ellipse Hough transform is characterized by comprising the following steps:

acquiring first measurement data of a radar station;

converting the first measurement data into second measurement data under a preset coordinate system; a preset elliptic equation is arranged under the preset coordinate system, and the preset elliptic equation has target parameters;

determining detection point data according to a preset quantization parameter, the preset ellipse equation and the second measurement data; the preset quantization parameter represents an estimated value of the target parameter;

and determining a tracking track of the target according to the detection point data.

2. The method for tracking the target based on the ellipse Hough transform as claimed in claim 1, wherein: the first measurement data is expressed by a spherical coordinate system, and the converting of the first measurement data into second measurement data under a preset coordinate system includes:

determining a first conversion relation between the spherical coordinate system and a transmitting coordinate system;

determining a second conversion relation between the emission coordinate system and the preset coordinate system according to the first conversion relation;

and converting the first measurement data into the second measurement data according to the first measurement data and the second conversion relation.

3. The method for tracking the target based on the ellipse Hough transform as claimed in claim 2, wherein: and determining the second conversion relationship between the transmission coordinate system and the second conversion relationship according to the first conversion relationship, wherein the formula for determining the second conversion relationship is as follows:

wherein r is_TFor the purpose of the predetermined coordinate system,a coordinate transformation matrix r for said emission coordinate system and said predetermined coordinate system_LCFor characterizing said first conversion relation, ξ₃＝(0,r_o+H,0)^T，r_oIs the earth mean radius, H is the height of the radar station, and T is the transpose.

4. The method for tracking the target based on the ellipse Hough transform as claimed in claim 1, wherein: the acquiring of the first measurement data of the radar station includes:

sequentially scanning through a radar search window with a preset size according to wave positions to obtain a plurality of frames of detection data, wherein each frame of detection data comprises a plurality of traces; the first metrology data includes a number of frames of the probing data.

5. The method for tracking the target based on the ellipse Hough transform as claimed in claim 1, wherein: the target parameters comprise a long half shaft parameter and a short half shaft parameter, the preset quantization parameters comprise a first quantization parameter and a second quantization parameter, and the preset quantization parameters are determined through the following steps:

determining a search area of the target parameter;

discretizing the search area;

determining a first resolution and a second resolution according to a discretization result and the search area;

determining the first quantization parameter of the long half axis parameter according to the discretization result and the first resolution, and determining the second quantization parameter of the short half axis parameter according to the discretization result and the second resolution.

6. The method for tracking the target based on the ellipse Hough transform as claimed in claim 5, wherein: the determining a first resolution and a second resolution from the discretization result and the search region includes:

determining the first resolution according to the ratio of the first length to the first value, and determining the second resolution according to the ratio of the second length to the second value; the first length and the second length are determined according to the range of the semi-major axis parameter and the range of the semi-minor axis parameter in the search area respectively, and the first value and the second value are determined according to the number of the first length and the number of the second length after discretization respectively.

7. The method for tracking the target based on the ellipse Hough transform as claimed in claim 5, wherein: determining detection point data according to a preset quantization parameter, the preset ellipse equation and the second measurement data, including:

determining a first calculation result of the minor half shaft parameter according to the second measurement data, each first quantization parameter and the preset ellipse equation;

calculating an absolute value of a difference between the second quantization parameter and the first calculation result;

accumulating the threshold parameters according to the absolute values;

and when the accumulated threshold parameter is greater than or equal to a preset secondary detection threshold, determining the detection point data.

8. The method for tracking the target based on the ellipse Hough transform as claimed in claim 7, wherein: accumulating the threshold parameters according to the absolute values, including:

accumulating a fixed value for the threshold parameter every time the absolute value is less than or equal to half of the second resolution;

alternatively, the first and second electrodes may be,

accumulating a variation value for the threshold parameter every time the absolute value is less than or equal to half the second resolution; the variation value is determined according to a preset weighting coefficient and the second measurement data.

9. The method for tracking the target based on the ellipse Hough transform as claimed in claim 5, wherein: the determining a tracking track of the target according to the detection point data includes:

when the detection point data comprises a detection point, carrying out coordinate inverse transformation on the first quantization parameter and the second quantization parameter corresponding to the detection point to obtain a tracking track of a target;

alternatively, the first and second electrodes may be,

when the detection point data comprises a plurality of detection points, clustering the plurality of detection points into a preset number of points;

and respectively carrying out coordinate inverse transformation on the first quantization parameter and the second quantization parameter corresponding to the preset number of points to obtain a tracking track of the target.

10. An ellipse Hough transform-based target tracking system, comprising:

the acquisition module is used for acquiring first measurement data of the radar station;

the conversion module is used for converting the first measurement data into second measurement data under a preset coordinate system; a preset elliptic equation is arranged under the preset coordinate system, and the preset elliptic equation has target parameters;

the detection point data determining module is used for determining detection point data according to a preset quantization parameter, the preset elliptic equation and the second measurement data; the preset quantization parameter represents an estimated value of the target parameter;

and the tracking track determining module is used for determining the tracking track of the target according to the detection point data.

Technical Field

The invention relates to the technical field of radars, in particular to a target tracking method and a target tracking system based on ellipse Hough transform.

Background

Hough (Hough) transformation is applied to straight line detection in images at first, and then introduced into the field of radar data processing, and is mainly used for track-before-detect (TBD) anti-stealth. However, for the trajectory detection of a target by Radar data processing, a classical straight line Hough transform is generally used, and the straight line Hough transform is only suitable for the trajectory detection in a short time, but for a ballistic target, the motion trajectory is a space curve, and the Radar Cross Section (RCS) of the ballistic target can be as small as 0.00009. Therefore, the linear Hough transform is difficult to obtain a good TBD detection effect, and it cannot effectively detect and track a ballistic target.

Disclosure of Invention

In view of the above, in order to solve the above technical problems, an object of the present invention is to provide a target tracking method and system based on an elliptic hough transform, which can track a ballistic target.

The technical scheme adopted by the invention is as follows:

a target tracking method based on ellipse Hough transform comprises the following steps:

acquiring first measurement data of a radar station;

converting the first measurement data into second measurement data under a preset coordinate system; a preset elliptic equation is arranged under the preset coordinate system, and the preset elliptic equation has target parameters;

determining detection point data according to a preset quantization parameter, the preset ellipse equation and the second measurement data; the preset quantization parameter represents an estimated value of the target parameter;

and determining a tracking track of the target according to the detection point data.

Further, the step of converting the first measured data into second measured data in a preset coordinate system, where the first measured data is represented by a spherical coordinate system, includes:

determining a first conversion relation between the spherical coordinate system and a transmitting coordinate system;

determining a second conversion relation between the emission coordinate system and the preset coordinate system according to the first conversion relation;

and converting the first measurement data into the second measurement data according to the first measurement data and the second conversion relation.

Further, the determining the second transformation relationship according to the first transformation relationship may be performed by:

wherein r is_TFor the purpose of the predetermined coordinate system,a coordinate transformation matrix r for said emission coordinate system and said predetermined coordinate system_LCFor characterizing said first conversion relation, ξ₃＝(0,r_o+H,0)^T，r_oIs the earth mean radius, H is the height of the radar station, and T is the transpose.

Further, the acquiring of the first measurement data of the radar station specifically includes:

sequentially scanning through a radar search window with a preset size according to wave positions to obtain a plurality of frames of detection data, wherein each frame of detection data comprises a plurality of traces; the first metrology data includes a number of frames of the probing data.

Further, the target parameters include a major axis parameter and a minor axis parameter, the preset quantization parameters include a first quantization parameter and a second quantization parameter, and the preset quantization parameters are determined by the following steps:

determining a search area of the target parameter;

discretizing the search area;

determining a first resolution and a second resolution according to a discretization result and the search area;

determining the first quantization parameter of the long half axis parameter according to the discretization result and the first resolution, and determining the second quantization parameter of the short half axis parameter according to the discretization result and the second resolution.

Further, the determining a first resolution and a second resolution according to the discretization result and the search area includes:

determining the first resolution according to the ratio of the first length to the first value, and determining the second resolution according to the ratio of the second length to the second value; the first length and the second length are determined according to the range of the semi-major axis parameter and the range of the semi-minor axis parameter in the search area respectively, and the first value and the second value are determined according to the number of the first length and the number of the second length after discretization respectively.

Further, the determining the detection point data according to the preset quantization parameter, the preset ellipse equation and the second measurement data includes:

determining a first calculation result of the minor half shaft parameter according to the second measurement data, each first quantization parameter and the preset ellipse equation;

calculating an absolute value of a difference between the second quantization parameter and the first calculation result;

accumulating the threshold parameters according to the absolute values;

and when the accumulated threshold parameter is greater than or equal to a preset secondary detection threshold, determining the detection point data.

Further, the accumulating the threshold parameter according to the absolute value includes:

accumulating a fixed value for the threshold parameter every time the absolute value is less than or equal to half of the second resolution;

alternatively, the first and second electrodes may be,

accumulating a variation value for the threshold parameter every time the absolute value is less than or equal to half the second resolution; the variation value is determined according to a preset weighting coefficient and the second measurement data.

Further, the determining a tracking trajectory of a target according to the detection point data includes:

when the detection point data comprises a detection point, carrying out coordinate inverse transformation on the first quantization parameter and the second quantization parameter corresponding to the detection point to obtain a tracking track of a target;

alternatively, the first and second electrodes may be,

when the detection point data comprises a plurality of detection points, clustering the plurality of detection points into a preset number of points;

and respectively carrying out coordinate inverse transformation on the first quantization parameter and the second quantization parameter corresponding to the preset number of points to obtain a tracking track of the target.

The invention also provides a target tracking system based on the ellipse Hough transform, which comprises the following components:

the acquisition module is used for acquiring first measurement data of the radar station;

the conversion module is used for converting the first measurement data into second measurement data under a preset coordinate system; a preset elliptic equation is arranged under the preset coordinate system, and the preset elliptic equation has target parameters;

the detection point data determining module is used for determining detection point data according to a preset quantization parameter, the preset elliptic equation and the second measurement data; the preset quantization parameter represents an estimated value of the target parameter;

and the tracking track determining module is used for determining the tracking track of the target according to the detection point data.

The invention has the beneficial effects that: the acquired first measurement data of the radar station are converted into second measurement data under a preset coordinate system for processing, and detection point data are determined according to a preset elliptic equation, preset quantitative parameters and the second measurement data under the preset coordinate system which accords with the trajectory of the ballistic target, so that the tracking trajectory of the target is determined, and the ballistic target can be detected and tracked.

Drawings

FIG. 1 is a schematic flow chart illustrating steps of a target tracking method based on an ellipse Hough transform according to the present invention;

fig. 2(a) is a schematic diagram of a detection point when the preset secondary detection threshold is 2.5 according to the embodiment of the present invention, and fig. 2(b) is a schematic diagram of a detection point when the preset secondary detection threshold is 1 according to the embodiment of the present invention;

fig. 3(a) is a schematic diagram of a trajectory when the predetermined secondary detection threshold is 2.5 according to an embodiment of the present invention, and fig. 3(b) is a schematic diagram of a trajectory when the predetermined secondary detection threshold is 1 according to an embodiment of the present invention.

Detailed Description

In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The terms "first," "second," "third," and "fourth," etc. in the description and claims of this application and in the accompanying drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.

As shown in fig. 1, an embodiment of the present application provides a target tracking method based on an elliptic hough transform, which may include the following steps:

and S1, acquiring first measurement data of the radar station.

In this embodiment of the application, the first measurement data is represented by a spherical coordinate system, and the obtaining of the first measurement data specifically may be:

the method comprises the steps of sequentially scanning through a radar search window with a preset size according to wave positions to obtain a plurality of frames of detection data, wherein each frame of detection data comprises a plurality of traces, and the first measurement data comprises the plurality of frames of detection data. In the embodiment of the present application, N frames of (raw) sounding data are obtainedZ_1:NRepresenting each frame of detection data, the number of traces of each frame is m_iThe total measurement trace is

S2, converting the first measurement data into second measurement data in a predetermined coordinate system.

In the embodiment of the application, a preset elliptic equation is provided under the preset coordinate system, and the preset elliptic equation has target parameters. It should be noted that the preset coordinate system is a coordinate system designed in the embodiment of the present application, the preset ellipse equation is established according to the coordinate representation of the preset coordinate system, and the target parameters include a semi-major axis parameter a of the ellipse and a semi-minor axis parameter b of the ellipse. The preset elliptic equation Γ is specifically as follows:

y_t≥0,z_t＝0

wherein x is_t y_t z_tIs a coordinate representation of a predetermined coordinate system, r_oThe average radius of the earth, h is the height of the shutdown point, and theta is the middle range angle. It should be noted that the trajectory of a ballistic target is only a portion of the arc length of an elliptical orbit, and not the entire ellipse. Therefore, the classical elliptic Hough transformation based on the dual method is not suitable for the stealth ballistic target, and the subsequent processing is required to be performed by using the processing method of the embodiment of the application. In the preset coordinate system, the y axis is the highest point pointed by the geocenter, the x axis is the tangent direction of the highest point, and the right-hand system is formed by the z axis, the x axis and the y axis.

Since the actual radar is generally described in the radar station spherical coordinate system when searching in the window, an association relationship between the radar measurement value (first measurement data) and a preset elliptic equation needs to be established.

Specifically, step S2 may include the steps of:

and S21, determining a first conversion relation between the spherical coordinate system and the emission coordinate system.

In the embodiment of the application, a first relation between a spherical coordinate system and an ENU rectangular coordinate system (station center rectangular coordinate system) of a radar station is determined, a second relation between the ENU rectangular coordinate system and a ground center fixed connection ECF coordinate system is determined, and a first conversion relation between the spherical coordinate system and a transmitting coordinate system is determined according to a third relation between the ground center fixed connection ECF coordinate system and the transmitting coordinate system.

Specifically, one frame of the probe dataRadar station ENU rectangular coordinate system (standing center rectangular coordinate system)The first relation with the spherical coordinate system is as follows:

wherein R is distance, A is azimuth, E is elevation, x, y, z represent R_ENUIn the coordinate representation in the coordinate system, it should be noted that T in the embodiment of the present application is represented by transpose.

ECF coordinate system r of earth core fixed connection_ECF＝(x_e,y_e,z_e)^TThe conversion relation with the ENU coordinate system is as follows:

in which ξ₁＝(0,0,r_o+H)^TAnd H is the height of the radar station,is a coordinate transformation matrix from ENU coordinate system to ECF coordinate system, x_e、y_e、z_eIs a coordinate representation in an ECF coordinate system, specifically:

in the above formula R_i(·), (i ═ X, Y, Z) is a coordinate rotation matrix, L is the longitude of the radar station, and B is the latitude of the radar station. ECF coordinate system and emission LC coordinate system (emission coordinate system r)_LC) Has a conversion relation of

WhereinFor coordinate transformation matrix from ECF coordinate system to LC coordinate system, note A₀For transmitting the earth azimuth, L_CAnd B_CLatitude and longitude of the shutdown point, ξ₂Is the position vector of the shutdown point in the ECF coordinate system, thenThe specific expression of (A) is as follows:

thus, the first conversion relation between the spherical coordinate system and the emitting coordinate system can be obtained by substituting the first relation.

And S22, determining a second conversion relation between the emission coordinate system and the preset coordinate system according to the first conversion relation. An emission coordinate system and

predetermined coordinate system r_T＝(x_t,y_t,z_t)^TThe second conversion relation of (2) is:

wherein r is_TIs a pre-set coordinate system, and is,is a coordinate transformation matrix of the emission coordinate system and the preset coordinate system, r_LCFor characterizing the first conversion relation, xi₃＝(0,r_o+H,0)^T，r_oIs the earth's mean radius, H is the radar station's height, and T is the transpose.

Therefore, after the arrangement, the relation between the spherical coordinate system and the preset coordinate system can be obtained as follows:

thus, radar measurement vectors Z (a frame of detection data) and r can be established_TCan be written asIn the form of (1), wherein A₀,θ,ξ₂The estimated value can be provided by early warning information, D is radarThe size of the search window, and therefore the implicit relation equation of the first metrology data to the elliptical trajectory equation (the preset elliptical equation) can be written as:

Γ:φ(a,b；R,A,E；A₀,θ,ξ₂)＝0,[R,A,E]∈D

s23, converting the first measurement data into second measurement data according to the first measurement data and the second conversion relation.

It is understood that the first measurement data passes through the spherical coordinate system and the predetermined coordinate system (r)_T) The relationship (c) can be converted into second measurement data in the preset coordinate system.

In the embodiment of the present application, a step of determining a preset quantization parameter is further included, where the preset quantization parameter refers to a quantization parameter determined by a preset rule, and it can be understood that the preset quantization parameter may also be a quantization parameter within a certain range.

Optionally, in this embodiment of the application, the target parameter includes a major axis parameter and a minor axis parameter, and the preset quantization parameter includes a first quantization parameter and a second quantization parameter. With a parametric coordinate system (a)_t,b_t) And transforming the preset elliptic equation to obtain:

wherein, at this time (a)_t,b_t) Is a variable in a preset coordinate system, x_tAnd y_tIs a parameter in a preset coordinate system. The curve shown in the above equation becomes a planar quartic curve, and thus, in the parameter space, there will be an accumulation of a series of quartic curves, whose centers of aggregation are the true parameters (a, b).

Optionally, the preset quantization parameter determining step includes the following steps S101 to S104:

s101, determining a search area of the target parameter.

In the examples of the present application, let a × b ∈ [ a ]_L,a_U]×[b_L,b_U]A search area of the target parameter space is defined, it should be noted that the search area can be generalThe radar system of the passing radar station provides or is set up with a priori information. Wherein, a_L、a_U、b_L、b_UIs a numerical value of_U-a_LIs a first length, b_U-b_LIs the second length. It can be seen that the first length and the second length are determined according to the range of the major axis parameter and the range of the minor axis parameter in the search region, respectively.

S102, discretizing the search area.

In the embodiment of the application, the parameter space is discretized according to the preset interval to obtain n_a×n_bA lattice, wherein n_aThe number of the first length after being divided is recorded as a first value, n_bThe number of the second length divided by the average is recorded as a second value. It can be seen that the first and second values are determined according to the number of the first length divided and the number of the second length divided after the discretization, respectively.

S103, determining a first resolution and a second resolution according to the discretization result and the search area.

In the embodiment of the present application, the first resolution is determined according to a ratio of the first length to the first value, and the second resolution is determined according to a ratio of the second length to the second value.

Specifically, the formula is: Δ a ═ a_U-a_L)/n_a，Δb＝(b_U-b_L)/n_bWhere Δ a is the first resolution and Δ b is the second resolution.

And S104, determining a first quantization parameter of the long half-axis parameter according to the discretization result and the first resolution, and determining a second quantization parameter of the short half-axis parameter according to the discretization result and the second resolution.

Specifically, the formula is:

a(i)＝(n_a-1/2)Δa,i＝1,…,n_a

b(j)＝(n_b-1/2)Δb,j＝1,…,n_b

wherein, a (i) is a first quantization parameter, b (j) is a second quantization parameter, the first quantization parameter represents the estimated value of the major-semiaxis parameter a, and the second quantization parameter represents the estimated value of the minor-semiaxis parameter b.

And S3, determining the detection point data according to the preset quantization parameter, the preset ellipse equation and the second measurement data.

Alternatively, step S3 may include the following steps S31-S34:

s31, determining a first calculation result of the minor-half axis parameter according to the second measurement data, each first quantization parameter and a preset ellipse equation.

In particular, based on a priori information provided by the radar systemIn order to transmit an estimate of the azimuth of the earth,is an estimate of the mid-range angle, ξ₂The position vector of the shutdown point in the ECF coordinate system is combined with a preset elliptic equation to determine the conversion value of the first measurement data in the preset coordinate system, namely the second measurement datak is 1, …, m, whereinAre values on different coordinate axes of the second measurement data represented by a preset coordinate system.

After the second measurement data are obtained, determining the minor axis (first calculation result) b (i, k) of the minor axis parameter by combining each first quantization parameter and a preset ellipse equation according to the following formula:

i＝1,…,n_a,k＝1,…,m

and S32, calculating the absolute value of the difference value of the second quantization parameter and the first calculation result.

Specifically, the absolute value is | b (j) -b (i, k) |.

And S33, accumulating the threshold parameters according to the absolute values.

In the embodiment of the present application, the threshold parameter c (i, j) has an initial value, specifically: c (i, j) is 0, i is more than or equal to 1 and less than or equal to n_a,1≤j≤n_bI, j e N, the accumulation of the threshold parameter c (i, j) can optionally be done in two ways:

1) and (3) uniform weighting: for each value of k, c (i, j) is counted every time b (i, k) satisfies | b (j) | ≦ Δ b/2, and a fixed value is accumulated, which is taken as an example that the fixed value is equal to 1 in the embodiment of the present application, i.e., c (i, j) ≦ c (i, j) + 1.

2) Non-uniform weighting: for each value of k, whenever b (i, k) satisfies | b (j) -b (i, k) | ≦ Δ b/2, counting c (i, j), accumulating the change value, optionally the change value isNamely, it isWherein q is a preset weighting coefficient, and when q → ∞,the degradation is now in a uniformly weighted form; if the point is the point on the target trajectory, transforming the point to a preset coordinate systemIs zero-mean and is affected only by noise, and is therefore of zero-mean valueClose to 1, while clutter and false alarm are non-planar after transformation due to random distribution,is relatively large, thereforeThe ratio is small, so when q is large, the ballistic target and the false alarm can be well inhibited, in the embodiment of the application, q is 0.01-0.0001, and the ratio isThe test shows that the effect is better.

And S34, determining the detection point data when the accumulated threshold parameter is greater than or equal to the preset secondary detection threshold.

In the embodiment of the application, a preset secondary detection threshold eta is set^HoughWhen the accumulated threshold parameter c (i, j) is greater than or equal to eta^HoughOne detection point may be obtained and a plurality of detection points may be obtained by a plurality of comparisons similarly, so it is understood that the detection point data includes at least one detection point. In the embodiment of the application, the preset secondary detection threshold eta is^HoughSet to 2.5, it will be appreciated that in practice adjustments may be made.

It can be understood that the threshold parameter after the accumulation is greater than or equal to the preset quadratic detection threshold eta^HoughDetermining a detection point, thus presetting a secondary detection threshold eta^HoughDirectly determines the detection probability of the target track as a key parameterAnd false alarm probabilityThe size of (2). When eta^HoughThe higher the setting, the greater the probability of detecting the actual trajectory; eta^HoughWith the lower setting, false ballistics are easily detected. In practice, the detection performance is also related to the distribution of the target and clutter, and also to the first detection threshold η and the signal-to-noise ratio S. When the first threshold η is set to be lower, more clutter will pass through the first threshold, and therefore, the second threshold η^HoughIt needs to be improved properly to effectively eliminate the peak due to clutter. While the amplitude of clutter or false alarms is generally considered to be a Rayleigh distribution, the target is generally considered to be a SwerlingII distribution. Under the above conditions, the distribution of the clutter normalized power is an exponential distribution, and the density function f (x) is:

f(x)＝e^-x

the distribution density f (x | S) of the target power is:

f(x|S)＝exp(-x/(1+S))/(1+S)

wherein S is the signal-to-noise ratio, the detection probability P of a single target trace point_dComprises the following steps:

in the above formulaFor the detection threshold (square law detection) of a single trace point, the false alarm probability P of the single trace point_faThe higher the detection threshold η is, the lower. In order to achieve the purpose of anti-stealth, a relatively small value needs to be set for the primary detection threshold eta of a single point trace, so that the detection probability P of the target point trace is ensured_dIs relatively high. For example, when P_faWhen the signal-to-noise ratio S is 10dB and 0.1, the detection probability of a single target trace point is P_d＝0.81113。

Recording the power (x) of k data in a quantization unit in the parameter space_iI ═ 1,2, …, k) exceeds a threshold η, the probability of occurrence isWhere m is the total number of valid traces, the accumulated energy in a unit exceeds eta^HoughThe probability of (c) is:

wherein c is the accumulated value of the parameter space, c_iFor the accumulated value of the ith data point, c is the average weight_i1, and for non-uniform weightingAre values on different coordinate axes of the second measurement data represented by a preset coordinate system. In the above formula mn_aThe maximum number of accumulations in a cell, since each case may occur, is added in a permutation and combinationy represents that the energy accumulation value of the ith data point exceeds eta^Hough，Is P_dThe probability of corresponding different values of k. The probability of detection in the first way (uniformly weighted) is:

whereinRepresenting a rounding operation. And the probability of detection for the second mode (non-uniform weighting) is:

due to the fact thatIs very difficult to calculate, thereforeIt is also difficult to have an analytical solution. Calculating the detection probabilityRear, false alarm probabilityThe SNR S → 0 is only required.

In summary, it can be seen that the detection probability of the target track in a certain resolution unitWith a first detection threshold eta and a second detection threshold eta^HoughSignal-to-noise ratio S, resolution of parameter quantization (n)_aOr n_b) The total number m of processed data points (which is related to the tracking data rate and the frame length N), the radar measurement precision (which affects the aggregation effect), and the like.

Referring to FIGS. 2(a) and 2(b), it can be seen that at η^HoughWhen the ratio is higher, the clustering center is very close to the true value point, so the detection effect is better, and the detection probability of the trajectory is high; but when eta^HoughAt low, due to the influence of noise and measurement noise, many false peaks are inevitably detected, and the detection result will deviate from the true parameter value. Thus, referring to FIGS. 3(a) and 3(b), when η^HoughAt higher, the detected trajectory and the true trajectory are substantially coincident, with only a slight offset (due to clutter and measurement errors); when eta is^HoughAt the lower achievement, the detected trajectory has gradually deviated from the true trajectory, i.e. from the true parameter value. Eta. to be noted^HoughNot higher as better, η^HoughSmaller is proportional to the detection probability, but when η^HoughTo some extent, there is a possibility that one peak point will not be detected, which will cause trajectory miss detection, so η^HoughIn the embodiment of the application, the value is 2.5, and the adjustment and the improvement can be continuously performed in practical situations.

And S4, determining the tracking track of the target according to the detection point data.

Alternatively, step S4 may be implemented by step S41 or step S42:

s41, when the detection point data comprises a detection point, carrying out coordinate inverse transformation on a first quantization parameter and a second quantization parameter corresponding to the detection point to obtain a tracking track of the target;

specifically, when a detected point is determined in step S34, specific values of the first quantization parameter and the second quantization parameter corresponding to the detected point can be found and used as the estimated parameters according to the position of the detected point, and the first estimated parameter isSecond estimated parametersAnd performing inverse coordinate conversion on the first estimation parameter and the second estimation parameter to obtain a detection trajectory of the target in a PPI coordinate system or an ENU coordinate, namely the tracking track of the target.

S42, clustering the detection points into a preset number of points when the detection point data comprises a plurality of detection points; and respectively carrying out coordinate inverse transformation on the first quantization parameter and the second quantization parameter corresponding to the preset number of points to obtain the tracking track of the target.

Specifically, when the detection point data has a plurality of detection points, for example, k is obtained_cA detection pointk＝1,…,k_cThen, a nominal preset (target) number k is set_tWill bePerforming K-means clustering to obtain K_tThe point can be found by the method of step S41 as the first quantization parameter and the second quantization parameter corresponding to the detection point and used as the estimation parameter, wherein The first estimation parameter and the second estimation parameter are respectively. In the embodiment of the application, under the influence of measurement noise, a Hough transform method is easy to generate a false alarm near the highest point, so that a plurality of detection points are subjected to K-means clustering, and only one detection point near the highest point can be ensured to a certain extent.

In addition, by the determined target tracking track of the embodiment of the application, the subsequent target trajectory prediction and the subsequent target trajectory drop point estimation can be performed.

The invention also provides a target tracking system based on the ellipse Hough transform, which comprises the following components:

the acquisition module is used for acquiring first measurement data of the radar station;

the conversion module is used for converting the first measurement data into second measurement data under a preset coordinate system; a preset elliptic equation is arranged under a preset coordinate system, and the preset elliptic equation has target parameters;

the detection point data determining module is used for determining detection point data according to a preset quantization parameter, a preset elliptic equation and second measurement data; presetting an estimated value of a quantization parameter representation target parameter;

and the tracking track determining module is used for determining the tracking track of the target according to the detection point data.

The contents in the above method embodiments are all applicable to the present system embodiment, the functions specifically implemented by the present system embodiment are the same as those in the above method embodiment, and the beneficial effects achieved by the present system embodiment are also the same as those achieved by the above method embodiment.

The embodiment of the invention also provides equipment, which comprises a processor and a memory;

the memory is used for storing programs;

the processor is used for executing programs to realize the target tracking method based on the ellipse Hough transform. The device provided by the embodiment of the invention can realize the function of target tracking based on the ellipse Hough transform.

The contents in the above method embodiments are all applicable to the present apparatus embodiment, the functions specifically implemented by the present apparatus embodiment are the same as those in the above method embodiments, and the beneficial effects achieved by the present apparatus embodiment are also the same as those achieved by the above method embodiments.

In summary, compared to the prior art, the present invention has at least the following advantages:

1) the weak space target TBD method based on the hough transform takes the hough transform and a TBD algorithm as the basis, converts the measurement value into a preset coordinate system for processing, can well inhibit noise and clutter, and improves detection performance.

2) According to the motion characteristics of the ballistic target, the elliptic Hough transform is suitable for processing long-time observation data in the middle section of the whole ballistic target track, the fusion of detection, tracking and prediction is realized, and the defects of the standard Hough transform are overcome.

3) The method can better inhibit noise and clutter, adopts a non-uniform weighting mode in parameter accumulation, and compared with the uniform weighting accumulation effect, the peak points of the non-uniform weighting accumulation result are distributed in a needle shape and are less influenced by the noise and the clutter. After the weighting factor is adopted, the weight of a point deviating from the ballistic plane (namely clutter) is inhibited to a greater degree, so that the accumulation effect is better.

4) The requirement on the signal-to-noise ratio is reduced, and when the signal-to-noise ratio is 0 or lower, weak targets such as trajectories can be detected according to a certain probability, so that the estimation accuracy is reduced. While the conventional sequential tracking method generally requires a signal-to-noise ratio of more than 13dB to maintain stable tracking. The embodiment of the application can still partially work under the condition of 0dB, so that the method of the embodiment of the application has the advantage of anti-stealth.

The terms "first," "second," "third," "fourth," and the like in the description of the application and the above-described figures, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

It should be understood that in the present application, "at least one" means one or more, "a plurality" means two or more. "and/or" for describing an association relationship of associated objects, indicating that there may be three relationships, e.g., "a and/or B" may indicate: only A, only B and both A and B are present, wherein A and B may be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one of the following" or similar expressions refer to any combination of these items, including any combination of single item(s) or plural items. For example, at least one (one) of a, b, or c, may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form. Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment. In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.