CN104166134A

CN104166134A - Real beam foresight scanning radar target two-dimension locating method

Info

Publication number: CN104166134A
Application number: CN201410422691.4A
Authority: CN
Inventors: 张寅�; 黄钰林; 王月; 李�杰; 武俊杰; 杨建宇; 李文超
Original assignee: University of Electronic Science and Technology of China
Current assignee: University of Electronic Science and Technology of China
Priority date: 2014-08-25
Filing date: 2014-08-25
Publication date: 2014-11-26

Abstract

The invention discloses a two-dimensional positioning method of a real-beam forward-looking scanning radar target, comprising the following steps: S1: Initializing imaging system parameters, calculating the distance between a target at any point in the imaging area and a moving platform, and setting simulation parameters of a real-beam scanning radar point target ; S2: Perform range matching filtering; S3: Perform range motion compensation processing; S4: Model the scanning radar azimuth echo signal; S5: Construct weighted least squares objective function; S6: Perform target azimuth positioning. The present invention utilizes the transmission signal and the antenna pattern parameter information to transform the target amplitude estimation problem into the problem of the optimal solution of the target function with respect to the weighted vector w _n , and solves the position information of the target azimuth dimension by solving the optimal solution of the target function; It effectively solves the problem of low positioning accuracy of the target azimuth dimension in the forward-looking area of the moving platform, and realizes the two-dimensional precise positioning of the distance dimension and azimuth dimension of the target in the forward-looking area of the moving platform.

Description

A two-dimensional positioning method for real-beam forward-looking scanning radar targets

技术领域technical field

本发明属于雷达技术领域，特别涉及一种实波束前视扫描雷达目标二维定位方法。The invention belongs to the technical field of radar, in particular to a two-dimensional positioning method for a real beam forward-looking scanning radar target.

背景技术Background technique

雷达由于不受恶劣天气因素的影响，并能够全天时工作，因此在军事侦察、海洋及水文观测、陆/海追踪与救援等军用和民用领域发挥了不可或缺的作用。对实现运动平台前视区域目标的精确定位，对敌我目标侦察与探测、目标追踪与打击、海面目标搜救等功能的实现具有重要的意义。Because radar is not affected by bad weather and can work around the clock, it plays an indispensable role in military and civilian fields such as military reconnaissance, ocean and hydrological observation, land/sea tracking and rescue. It is of great significance to realize the precise positioning of the target in the forward-looking area of the moving platform, and the realization of functions such as enemy and enemy target reconnaissance and detection, target tracking and strike, and sea surface target search and rescue.

运动平台前视区域目标的距离维高精度定位可以通过发射大带宽的线性调频信号和使用脉冲压缩技术处理实现。然而对于前视成像区域的方位维，由于平台与成像区域内目标相对运动产生的多普勒频率梯度几乎为零，使得现有的合成孔径等成像技术很难实现方位维目标的准确定位只能通过扫描成像的方式获得方位维目标的低精度定位结果。由于该方式目标位置的定位和和幅度的估计精度低，严重影响了运动平台的侦察、监视、定位和识别能力。The range-dimensional high-precision positioning of the target in the forward-looking area of the motion platform can be realized by transmitting a large-bandwidth chirp signal and processing it with pulse compression technology. However, for the azimuth dimension of the forward-looking imaging area, because the Doppler frequency gradient generated by the relative motion between the platform and the target in the imaging area is almost zero, it is difficult to achieve accurate positioning of the azimuth dimension target with existing synthetic aperture and other imaging technologies. The low-precision positioning results of azimuth-dimensional targets are obtained by means of scanning imaging. Due to the low accuracy of target position positioning and amplitude estimation in this way, the reconnaissance, surveillance, positioning and identification capabilities of the motion platform are seriously affected.

针对运动平台前视区域二维目标定位问题，特别是如何提高方位维目标的定位能力，一般采用两种方法。其一如文献：Blair W D,Brandt-Pearce M.Monopulse DOA estimation oftwo unresolved Rayleigh targets[J].Aerospace and Electronic Systems,IEEE Transactions on,2001,37(2):452-469.所采用单脉冲技术进行方位维处理。该技术基于单脉冲测角原理，主要适用于单个强点目标的定位，虽然对特定条件下的两点目标有效，但对于存在多散射中心的复杂目标环境下，目标定位会存在严重偏差，甚至会产生虚假目标等现象；其二如文献：Mahafza B R,Knight D L,Audeh N F.Forward-looking SAR imaging using a linear array withtransverse motion[C]//Southeastcon'93,Proceedings.,IEEE.IEEE,1993:4 p.的方法，该文章提出一种线性阵列合成孔径雷达前视成像方法，利用线性阵列与前视区域内目标之间的相对运动产生多普勒带宽，再利用匹配滤波技术实现目标方位定位。但该方法需要尽量长的线阵以增加孔径尺寸，同时，由于前视区域内目标的多普勒带宽很小，能够获得的目标定位精度依然有限。For the two-dimensional target positioning problem in the forward-looking area of the motion platform, especially how to improve the positioning ability of the azimuth dimension target, two methods are generally adopted. It is like the literature: Blair W D, Brandt-Pearce M. Monopulse DOA estimation of two unresolved Rayleigh targets[J]. Aerospace and Electronic Systems, IEEE Transactions on, 2001,37(2):452-469. The monopulse technique used Perform azimuth processing. This technology is based on the principle of single-pulse angle measurement, and is mainly suitable for the positioning of a single strong point target. Although it is effective for two-point targets under certain conditions, for complex target environments with multiple scattering centers, there will be serious deviations in target positioning, and even False targets and other phenomena will be generated; the second is the literature: Mahafza B R, Knight D L, Audeh N F. Forward-looking SAR imaging using a linear array withtransverse motion[C]//Southeastcon'93,Proceedings.,IEEE.IEEE , 1993: 4 p. method, this article proposes a linear array synthetic aperture radar forward-looking imaging method, using the relative motion between the linear array and the target in the forward-looking area to generate Doppler bandwidth, and then using matched filtering technology to achieve Target orientation. However, this method requires a linear array as long as possible to increase the aperture size. At the same time, due to the small Doppler bandwidth of the target in the forward-looking area, the target positioning accuracy that can be obtained is still limited.

发明内容Contents of the invention

本发明的目的在于克服现有技术的不足，提供一种通过求解目标函数的最优解求解出目标方位维的位置信息，有效的解决了运动平台前视作用区域中目标方位维定位精度低的问题，实现了运动平台前视区域目标距离维和方位维的二维精确定位的实波束前视扫描雷达目标二维定位方法。The purpose of the present invention is to overcome the deficiencies of the prior art, provide a method to obtain the position information of the target azimuth dimension by solving the optimal solution of the objective function, and effectively solve the problem of low positioning accuracy of the target azimuth dimension in the forward-looking area of the moving platform The problem is to realize the two-dimensional precise positioning method of the real-beam forward-looking scanning radar target in the distance and azimuth dimensions of the forward-looking area of the moving platform.

本发明的目的是通过以下技术方案来实现的：一种实波束前视扫描雷达目标二维定位方法，包括以下步骤：The purpose of the present invention is achieved by the following technical solutions: a real beam forward scanning radar target two-dimensional positioning method, comprising the following steps:

S1：成像系统参数初始化，计算成像区域任意点目标与运动平台的距离，设置实波束扫描雷达点目标仿真参数；S1: Initialize the parameters of the imaging system, calculate the distance between the target at any point in the imaging area and the moving platform, and set the simulation parameters of the real beam scanning radar point target;

S2：进行距离向匹配滤波；S2: Perform distance matched filtering;

S3：进行距离向运动补偿处理；S3: Perform distance motion compensation processing;

S4：对扫描雷达方位向回波信号进行建模；S4: Modeling the azimuth echo signal of the scanning radar;

S5：构造加权最小二乘目标函数；S5: Construct a weighted least squares objective function;

S6：进行目标方位定位。S6: Carry out target orientation positioning.

进一步地，所述的步骤S1中计算成像区域任意点目标与运动平台的距离的具体方法为：运动平台零时刻位置记为(0,0,h)，运动平台沿y轴运动，运动速度为V，目标相对平台的方位角记为q，雷达天线下视角记为雷达天线扫描速度记为ω；则t时刻时运动平台与场景中目标距离通过系统参数表示为：Further, the specific method for calculating the distance between the target at any point in the imaging area and the motion platform in the step S1 is as follows: the zero moment position of the motion platform is recorded as (0,0,h), the motion platform moves along the y-axis, and the motion speed is V, the azimuth angle of the target relative to the platform is denoted as q, and the angle of view under the radar antenna is denoted as The scanning speed of the radar antenna is recorded as ω; then the distance between the moving platform and the target in the scene at time t is expressed by system parameters as:

其中，R0为运动平台与目标之间的初始距离；Among them, R0 is the initial distance between the motion platform and the target;

设置实波束扫描雷达点目标仿真参数的具体方法为：假设在扫描区域中同一距离R处的不同方位采样位置上都幅值，令产生这些运动幅值的目标的位置参数为θ＝(θ₁,θ₂,...θ_N)，幅度参数为σ＝(σ₁,σ₂,...,σ_N)，雷达发射信号为线性调频信号，扫描雷达作用区域的回波经过相干解调记为S(t,τ)：The specific method for setting the simulation parameters of the real beam scanning radar point target is as follows: assuming that the sampling positions at different azimuths at the same distance R in the scanning area have amplitude values, let the position parameters of the targets that generate these motion amplitude values be θ=(θ ₁ ,θ ₂ ,...θ _N ), the amplitude parameter is σ=(σ ₁ ,σ ₂ ,...,σ _N ), the radar transmission signal is a chirp signal, and the echo of the scanning radar active area is coherently demodulated Denoted as S(t,τ):

$S S ((t t,, τ τ)) = = {Σ Σ}_{n no = = 11}^{N N} {σ σ}_{n no} \cdot \cdot a a (({θ θ}_{n no},, τ τ)) \cdot &Center Dot; rect rect ((t t - - \frac{22 {R R}_{00}}{c c})) \cdot &Center Dot; exp exp ((- - j j \frac{44 π π}{λ λ} R R ((τ τ)))) \cdot &Center Dot; exp exp ((jπK jπK {[[t t - - \frac{22 R R ((τ τ))}{00}]]}^{22}))$

其中，τ为距离向时间变量，rect(·)和a(·)分别代表距离时间窗和方位时间窗，K是发射信号的时间调频斜率，c为光速，R(τ)代表运动平台与成像区域内各目标之间的距离变化；Among them, τ is the range time variable, rect(·) and a(·) represent the range time window and azimuth time window respectively, K is the time frequency modulation slope of the transmitted signal, c is the speed of light, R(τ) represents the motion platform and imaging Changes in the distance between targets in the area;

扫描雷达成像区域的方位时间向量记为：The azimuth time vector of the scanning radar imaging area is recorded as:

T_a＝[-PRI·N_a/2,-PRI·(N_a/2-1),…,PRI·(N_a/2-1)]T _a ＝[-PRI · N _a /2, -PRI · (N _a /2-1),..., PRI · (N _a /2-1)]

距离时间向量为：The distance-time vector is:

T_r＝[-1/f_r·N_r/2,-1/f_r·(N_r/2-1),…,1f_r·(N_r/2-1)]T _r ＝[-1/ _fr ·N _r /2,-1/ _fr ·(N _r /2-1),...,1fr _· (N _r /2-1)]

其中f_r为距离向采样率，PRI为发射信号脉冲重复间隔，N_a为方位向采样点数，N_r为距离向采样点数。。Where f _r is the sampling rate in the range direction, PRI is the pulse repetition interval of the transmitted signal, N _a is the number of sampling points in the azimuth direction, and N _r is the number of sampling points in the range direction. .

进一步地，所述的步骤S2中距离向匹配滤波具体包括以下子步骤：Further, the range matched filtering in step S2 specifically includes the following sub-steps:

S21：对经过相干解调的回波S(t,τ)进行距离向脉冲压缩处理，获得距离维目标高分辨率，并通过距离向FFT得到距离向频域、方位向时域的回波信号S(f_r,τ)：S21: Perform range pulse compression processing on the coherently demodulated echo S(t,τ) to obtain high resolution of the target in the range dimension, and obtain echo signals in the range frequency domain and azimuth time domain through range FFT S(f _r ,τ):

$S S (({f f}_{r r},, τ τ)) = = {Σ Σ}_{n no = = 11}^{N N} {σ σ}_{n no} \cdot \cdot a a (({θ θ}_{n no} τ τ)) \cdot \cdot rect rect ((\frac{{f f}_{r r}}{B B})) \cdot \cdot exp exp {{- - j j \frac{44 π π (({f f}_{c c} + + {f f}_{r r}))}{c c} R R ((τ τ))}} \cdot &Center Dot; exp exp {{jπ jπ \frac{{f f}_{r r}^{22}}{K K}}};;$

S22：构造距离向匹配滤波函数H(f_r)：S22: Construct the range-wise matched filter function H(f _r ):

$H h (({f f}_{r r})) = = exp exp ((- - jπ jπ \frac{{f f}_{r r}^{22}}{K K}));;$

S23：将H(f_r)与回波信号S(f_r,τ)相乘得到距离压缩后的距离向频域、方位向时域的回波信号S₁(f_r,τ)：S23: Multiply H( _fr ) and the echo signal S( _fr ,τ) to obtain the echo signal S ₁ ( _fr ,τ) in the range frequency domain and azimuth time domain after range compression:

${S S}_{11} (({f f}_{r r},, τ τ)) = = {Σ Σ}_{n no = = 11}^{N N} {σ σ}_{n no} \cdot &Center Dot; a a (({θ θ}_{n no},, τ τ)) \cdot &Center Dot; rect rect ((\frac{{f f}_{r r}}{B B})) \cdot &Center Dot; exp exp {{- - j j \frac{44 π π (({f f}_{c c} + + {f f}_{r r}))}{c c} R R ((t t))}} . .$

进一步地，所述的步骤S3中进行距离向运动补偿处理具体包括以下子步骤：Further, the range motion compensation processing in step S3 specifically includes the following sub-steps:

S31：将步骤S1中的进行泰勒展开；S31: the step S1 Perform Taylor expansion;

S32：忽略展开后的距离关系表达式中的二次项，同时由于与较小，所以cosθ≈1，因此，使得R(x,y,t)≈R₀-Vt；S32: Ignore the quadratic term in the expanded distance relation expression, and at the same time due to the smaller, so cosθ≈1, therefore, making R(x,y,t)≈R ₀ -Vt;

S33：构造距离徙动因子H(f_r,t)：S33: Construct distance migration factor H( _fr ,t):

$H h (({f f}_{r r},, t t)) = = exp exp ((j j 22 π π \cdot &Center Dot; {f f}_{r r} \cdot &Center Dot; \frac{Vt Vt}{c c}));;$

S34：将H(f_r,t)与S₁(f_r,τ)相乘消除雷达平台运动造成的距离徙动，并进行距离向IFFT变换得到高距离定位精度和低方位定位精度的二维时域信号S₂(t,τ)：S34: Multiply H( _fr ,t) and S ₁ ( _fr ,τ) to eliminate the range migration caused by the movement of the radar platform, and perform range-to-IFFT transformation to obtain a two-dimensional position with high range positioning accuracy and low azimuth positioning accuracy Time domain signal S ₂ (t,τ):

${S S}_{22} ((t t,, τ τ)) \approx \approx {Σ Σ}_{n no = = 11}^{N N} {σ σ}_{n no} \cdot \cdot a a (({θ θ}_{n no},, τ τ)) \cdot \cdot exp exp ((- - j j \frac{44 π π}{λ λ} {R R}_{00})) \cdot \cdot sin sin c c [[B B ((τ τ - - \frac{{22 R R}_{00}}{c c}))]] . .$

进一步地，所述的步骤S4中建模的具体方法为：对于各距离单元，方位扫描成像的回波模型及处理方式是相同的，因此任意选取任一距离单元的回波数据进行信号建模，方位向回波信号向量y表示为：Further, the specific method of modeling in step S4 is as follows: for each distance unit, the echo model and processing method of azimuth scanning imaging are the same, so the echo data of any distance unit is arbitrarily selected for signal modeling , the azimuth echo signal vector y is expressed as:

y＝A(θ)x+ny=A(θ)x+n

其中，为方向矩阵，由各个方位采样点对应的方向向量组成，a(n)＝[a₁，…，a_N]∈R^L×1为天线方向图序列，N为一个波束宽度的采样点数，x＝[x₁，...，x_N]表示方位向离散目标的幅度信息，M为方位向采样点数，y＝[y₁，...，y_M]为方位向接收的回波信号，n为附加噪声向量。in, is the direction matrix, which is composed of direction vectors corresponding to each azimuth sampling point, a(n)=[a ₁ ,...,a _N ]∈R ^L×1 is the antenna pattern sequence, N is the number of sampling points of a beam width, x =[x ₁ ,...,x _N ] represents the amplitude information of discrete targets in azimuth, M is the number of sampling points in azimuth, y=[y ₁ ,...,y _M ] is the echo signal received in azimuth, n is the additional noise vector.

进一步地，所述的步骤S5中构造加权最小二乘目标函数的具体方法为：对该距离单元的第n个目标，构造M×1维的加权向量w_n，令并建立求该目标幅值的目标函数的最小二乘解：Further, the specific method of constructing the weighted least squares objective function in the step S5 is as follows: construct an M×1-dimensional weighted vector w _n for the nth object of the distance unit, so that And establish the least squares solution of the objective function for the target magnitude:

$min min {{J J ((w w)) = = \frac{11}{K K} {Σ Σ}_{k k = = 11}^{K K} | | {w w}_{n no}^{H h} y the y ((k k)) - - {x x}_{n no} | |}}$

其中，K为扫描雷达扫过目标场景的扫描次数，x_n为第n个目标的幅值，展开目标函数得到：Among them, K is the number of times the scanning radar scans the target scene, x _n is the amplitude of the nth target, and the objective function is expanded to obtain:

$J J ((w w)) = = {w w}_{n no}^{H h} R R {w w}_{n no} - - \frac{11}{K K} {Σ Σ}_{k k = = 11}^{K K} | | {x x}_{n no} {w w}_{n no}^{H h} y the y ((k k)) - - {x x}_{n no} {y the y}^{H h} ((k k)) {w w}_{n no} | | + + {| | {x x}_{n no} | |}^{22}$

其中， $R = E {{yy}^{H}} = \frac{1}{K} Σ_{k = 1}^{K} y (k) y^{H} (k),$ 为信号的协方差矩阵，令 $g = \frac{1}{K} Σ_{k = 1}^{K} y (k),$ 则上式化简为：in, $R = E. {{yy}^{h}} = \frac{1}{K} Σ_{k = 1}^{K} the y (k) {the y}^{h} (k),$ is the covariance matrix of the signal, let $g = \frac{1}{K} Σ_{k = 1}^{K} the y (k),$ Then the above formula simplifies to:

$J J ((w w)) = = {w w}_{n no}^{H h} R R {w w}_{n no} + + {| | {x x}_{n no} - - {w w}_{n no}^{H h} g g | |}^{22} - - {w w}_{n no}^{H h} g g {g g}^{H h} {w w}_{n no} . .$

进一步地，所述的步骤S6中进行目标方位定位具体包括以下子步骤：Further, the target azimuth positioning in the step S6 specifically includes the following sub-steps:

S61：求等式 $J (w) = w_{n}^{H} R w_{n} + {| x_{n} - w_{n}^{H} g |}^{2} - w_{n}^{H} g g^{H} w_{n}$ 关于x_n的导数并令其导数为零，得到关于x_n幅度最优估计函数：S61: Find the equation $J (w) = w_{no}^{h} R w_{no} + {| x_{no} - w_{no}^{h} g |}^{2} - w_{no}^{h} g g^{h} w_{no}$ With respect to the derivative of x _n and making its derivative zero, the optimal estimation function of the amplitude of x _n is obtained:

${\overset{^^}{x x}}_{n no} = = {w w}_{n no}^{H h} g g;;$

S62：将等式的目标幅度最优估计函数代入到式 $J (w) = w_{n}^{H} R w_{n} + {| x_{n} - w_{n}^{H} g |}^{2} - w_{n}^{H} g g^{H} w_{n}$ 中，并令 $\hat{Q} = R - {gg}^{H},$ 得到重构后的目标函数：S62: Put the equation The optimal estimation function of the target amplitude is substituted into the formula $J (w) = w_{no}^{h} R w_{no} + {| x_{no} - w_{no}^{h} g |}^{2} - w_{no}^{h} g g^{h} w_{no}$ in, and make $\hat{Q} = R - {gg}^{h},$ Get the reconstructed objective function:

${J J}_{11} ((w w)) = = {w w}_{n no}^{H h} \overset{^^}{Q Q} {w w}_{n no} + + λ λ (({w w}_{n no}^{H h} h h (({θ θ}_{n no})) - - 11));;$

S63：求目标函数关J₁(w)关于加权向量w_n的最优解，其计算方法为：求目标函数关J₁(w)关于w_n的导数并令其为零，得到关于w_n的最优解：S63: Find the optimal solution of the objective function J ₁ (w) with respect to the weighted vector w _n , the calculation method is: find the derivative of the objective function J ₁ (w) with respect to w _n and make it zero, and obtain the optimal solution with respect to w _n The optimal solution for :

${w w}_{n no} = = \frac{{\overset{^^}{Q Q}}^{- - 11} h h (({θ θ}_{n no}))}{{h h}^{H h} (({θ θ}_{n no})) {\overset{^^}{Q Q}}^{- - 11} h h (({θ θ}_{n no}))};;$

S64：将w_n的计算结果代入到等式 $J (w) = w_{n}^{H} R w_{n} + {| x_{n} - w_{n}^{H} g |}^{2} - w_{n}^{H} g g^{H} w_{n}$ 中，得到关于x_n的幅度为：S64: Substituting the calculation result of w _n into the equation $J (w) = w_{no}^{h} R w_{no} + {| x_{no} - w_{no}^{h} g |}^{2} - w_{no}^{h} g g^{h} w_{no}$ , the magnitude of x _n is obtained as:

${\overset{^^}{x x}}_{n no} = = \frac{{h h}^{H h} (({θ θ}_{n no})) {\overset{^^}{Q Q}}^{- - 11} g g}{{h h}^{H h} (({θ θ}_{n no})) {\overset{^^}{Q Q}}^{- - 11} h h (({θ θ}_{n no}))};;$

S65：利用步骤S63和S64的方法计算出该距离单元的所有目标幅度，并定位目标的角度，实现目标方位维的精确定位，再将算法应用到整个扫描雷达作用区域中，逐距离单元对整个面目标场景处理，实现成像区域内目标的二维精确定位。S65: Utilize the methods of steps S63 and S64 to calculate all the target amplitudes of the range unit, and locate the angle of the target to realize the precise positioning of the target azimuth dimension, and then apply the algorithm to the entire scanning radar action area, and calculate the entire range unit by range unit. Surface target scene processing to achieve two-dimensional precise positioning of targets in the imaging area.

进一步地，所述的方位向采样点数M的计算方法为：Further, the calculation method of the number of azimuth sampling points M is:

$M m = = Φ Φ \frac{PRF PRF}{ω ω}$

其中，PRF为脉冲重复频率，ω为扫描速度，Φ为扫描范围。Among them, PRF is the pulse repetition frequency, ω is the scanning speed, and Φ is the scanning range.

本发明的有益效果是：本发明中采用实波束雷达以匀速扫描模式工作，雷达发射线性调频信号，利用发射信号和天线方向图参数信息，首先通过对回波信号的距离维匹配滤波处理获得目标距离维的精度定位，再进行运动补偿消除平台运动对回波信号的影响，实现目标距离维的高精度定位，随后建立实波束前视扫描雷达的信号回波模型，并基于加权最小二乘准则，构造了关于求解方位目标位置的目标函数，将目标幅度估计问题转化为目标函数关于加权向量w_n的最优解的问题，通过求解目标函数的最优解求解出目标方位维的位置信息；有效的解决了运动平台前视作用区域中目标方位维定位精度低的问题，最终实现了运动平台前视区域目标距离维和方位维的二维精确定位，与传统二维目标定位方法相比，目标方位维定位精度更高，幅度的复原更准确。本发明可以应用于动目标追踪、精确制导等领域。The beneficial effects of the present invention are: in the present invention, the real-beam radar is adopted to work in the uniform-speed scanning mode, and the radar transmits a chirp signal, and utilizes the transmission signal and the antenna pattern parameter information, firstly obtains the target through the range-dimension matched filter processing of the echo signal Accurate positioning in the distance dimension, and then perform motion compensation to eliminate the influence of platform motion on the echo signal, to achieve high-precision positioning in the distance dimension of the target, and then establish the signal echo model of the real-beam forward-looking scanning radar, and based on the weighted least squares criterion , constructing the objective function about solving the azimuth target position, transforming the target amplitude estimation problem into the optimal solution problem of the objective function about the weighted vector w _n , and solving the position information of the target azimuth dimension by solving the optimal solution of the objective function; It effectively solves the problem of low positioning accuracy of the target azimuth dimension in the forward-looking area of the moving platform, and finally realizes the two-dimensional accurate positioning of the distance and azimuth dimensions of the target in the forward-looking area of the moving platform. Compared with the traditional two-dimensional target positioning method, the target The positioning accuracy of the azimuth dimension is higher, and the recovery of the amplitude is more accurate. The invention can be applied to the fields of moving target tracking, precise guidance and the like.

附图说明Description of drawings

图1为本发明的定位方法流程图；Fig. 1 is the flowchart of positioning method of the present invention;

图2为本发明实施例采用的实波束扫描雷达成像系统结构图；Fig. 2 is the structural diagram of the real beam scanning radar imaging system adopted by the embodiment of the present invention;

图3为本发明的实施实施例采用的仿真目标场景布置图；FIG. 3 is a layout diagram of a simulation target scene adopted in an embodiment of the present invention;

图4为本发明的根据系统参数生成的二维回波信号；Fig. 4 is the two-dimensional echo signal generated according to the system parameters of the present invention;

图5为本发明实施例的距离向脉压后的数据加入SNR＝20dB高斯白噪声图形；Fig. 5 adds SNR=20dB Gaussian white noise pattern to the data after the distance phase pulse pressure of the embodiment of the present invention;

图6为本发明实施例的距离向脉压后数据加入SNR＝20dB高斯白噪声沿方位向的剖面图；Fig. 6 is the sectional view along the azimuth direction of adding SNR=20dB Gaussian white noise to the data after the pulse pressure of the distance phase according to the embodiment of the present invention;

图7为本发明的实施例图3中9个点目标进行二维目标定位处理的结果；Fig. 7 is the result of two-dimensional target positioning processing of nine point targets in Fig. 3 according to an embodiment of the present invention;

图8为本发明对应图6的处理结果沿方位向的剖面图。FIG. 8 is a sectional view along the azimuth direction corresponding to the processing result of FIG. 6 according to the present invention.

具体实施方式Detailed ways

下面结合附图和具体实施例进一步说明本发明的技术方案，但本发明所保护的内容不局限于以下所述。The technical solution of the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, but the protected content of the present invention is not limited to the following description.

如图1所示，一种实波束前视扫描雷达目标二维定位方法，包括以下步骤：As shown in Figure 1, a real-beam forward-looking scanning radar target two-dimensional positioning method includes the following steps:

S2：进行距离向匹配滤波；S2: Perform distance matched filtering;

S6：进行目标方位定位。S6: Perform target orientation positioning.

进一步地，所述的步骤S1中计算成像区域任意点目标与运动平台的距离的具体方法为：运动平台零时刻位置记为(0,0,h)，其中，0、0和h分别为接收站的x轴、y轴和z轴坐标；运动平台沿y轴运动，运动速度为V，目标相对平台的方位角记为θ，雷达天线下视角记为雷达天线扫描速度记为ω；则t时刻时运动平台与场景中目标距离通过系统参数表示为：Further, the specific method for calculating the distance between the target at any point in the imaging area and the moving platform in the step S1 is as follows: the position of the moving platform at zero time is recorded as (0,0,h), where 0, 0 and h are the received The x-axis, y-axis and z-axis coordinates of the station; the moving platform moves along the y-axis, the moving speed is V, the azimuth angle of the target relative to the platform is denoted as θ, and the angle of view under the radar antenna is denoted as The scanning speed of the radar antenna is recorded as ω; then the distance between the moving platform and the target in the scene at time t is expressed by system parameters as:

其中，R₀为运动平台与目标之间的初始距离；Among them, _R0 is the initial distance between the motion platform and the target;

设置实波束扫描雷达点目标仿真参数的具体方法为：假设在扫描区域中同一距离R处的不同方位采样位置上都幅值，令产生这些运动幅值的目标的位置参数为θ＝(θ₁,θ₂,...θ_N)，幅度参数为σ＝(σ₁,σ₂,...,σ_N)，雷达发射信号为线性调频信号，扫描雷达作用区域的回波经过相干解调记为S(t,τ)：The specific method for setting the simulation parameters of real beam scanning radar point targets is as follows: assuming that the sampling positions at different azimuths at the same distance R in the scanning area have amplitudes, let the position parameters of the targets that generate these moving amplitudes be θ=(θ ₁ ,θ ₂ ,...θ _N ), the amplitude parameter is σ=(σ ₁ ,σ ₂ ,...,σ _N ), the radar transmission signal is a chirp signal, and the echo of the scanning radar active area is coherently demodulated Denoted as S(t,τ):

$S S ((t t,, τ τ)) = = {Σ Σ}_{n no = = 11}^{N N} {σ σ}_{n no} \cdot &Center Dot; a a (({θ θ}_{n no},, τ τ)) \cdot &Center Dot; rect rect ((t t - - \frac{22 {R R}_{00}}{c c})) \cdot &Center Dot; exp exp ((- - j j \frac{44 π π}{λ λ} R R ((τ τ)))) \cdot &Center Dot; exp exp ((jπK jπK {[[t t - - \frac{22 R R ((τ τ))}{00}]]}^{22}))$

距离时间向量为：The distance-time vector is:

T_r＝[-1/f_r·N_r/2,-1/f_r·(N_r/2-1),…,1/f_r·(N_r/2-1)]T _r ＝[-1/f _r ·N _r /2,-1/f _r ·(N _r /2-1),...,1/f _r ·(N _r /2-1)]

其中f_r为距离向采样率，PRI为发射信号脉冲重复间隔，N_a为方位向采样点数，N_r为距离向采样点数。Where f _r is the sampling rate in the range direction, PRI is the pulse repetition interval of the transmitted signal, N _a is the number of sampling points in the azimuth direction, and N _r is the number of sampling points in the range direction.

$S S (({f f}_{r r},, τ τ)) = = {Σ Σ}_{n no = = 11}^{N N} {σ σ}_{n no} \cdot &Center Dot; a a (({θ θ}_{n no} τ τ)) \cdot &Center Dot; rect rect ((\frac{{f f}_{r r}}{B B})) \cdot \cdot exp exp {{- - j j \frac{44 π π (({f f}_{c c} + + {f f}_{r r}))}{c c} R R ((τ τ))}} \cdot \cdot exp exp {{jπ jπ \frac{{f f}_{r r}^{22}}{K K}}};;$

${S S}_{11} (({f f}_{r r},, τ τ)) = = {Σ Σ}_{n no = = 11}^{N N} {σ σ}_{n no} \cdot &Center Dot; a a (({θ θ}_{n no},, τ τ)) \cdot &Center Dot; rect rect ((\frac{{f f}_{r r}}{B B})) \cdot \cdot exp exp {{- - j j \frac{44 π π (({f f}_{c c} + + {f f}_{r r}))}{c c} R R ((t t))}} . .$

$H h (({f f}_{r r},, t t)) = = exp exp ((j j 22 π π \cdot \cdot {f f}_{r r} \cdot \cdot \frac{Vt Vt}{c c}));;$

S34：将H(f_r,t)与S₁(f_r,τ)相乘消除雷达平台运动造成的距离徙动，并进行距离向S34: Multiply H( _fr ,t) and S ₁ ( _fr ,τ) to eliminate the range migration caused by the movement of the radar platform, and perform range

IFFT变换得到高距离定位精度和低方位定位精度的二维时域信号S₂(t,τ)：The two-dimensional time-domain signal S ₂ (t,τ) with high distance positioning accuracy and low azimuth positioning accuracy is obtained by IFFT transformation:

${S S}_{22} ((t t,, τ τ)) \approx \approx {Σ Σ}_{n no = = 11}^{N N} {σ σ}_{n no} \cdot &Center Dot; a a (({θ θ}_{n no},, τ τ)) \cdot &Center Dot; exp exp ((- - j j \frac{44 π π}{λ λ} {R R}_{00})) \cdot &Center Dot; sin sin c c [[B B ((τ τ - - \frac{{22 R R}_{00}}{c c}))]] . .$

y＝A(θ)x+ny=A(θ)x+n

${\overset{^^}{x x}}_{n no} = = {w w}_{n no}^{H h} g g;;$

S63：通过上述操作，将目标幅度估计问题转化为求目标函数J₁(w)关于加权向量w_n的最优解问题，求目标函数关J₁(w)关于加权向量w_n的最优解的计算方法为：求目标函数关J₁(w)关于w_n的导数并令其为零，得到关于w_n的最优解：S63: Through the above operations, transform the target amplitude estimation problem into the problem of finding the optimal solution of the objective function J ₁ (w) with respect to the weighted vector w _n , and find the optimal solution of the objective function J ₁ (w) with respect to the weighted vector w _n The calculation method of is: find the derivative of the objective function J ₁ (w) with respect to w _n and make it zero, and obtain the optimal solution with respect to w _n :

$M m = = Φ Φ \frac{PRF PRF}{ω ω}$

下面结合具体实施例对本发明的技术方案进行进一步说明，主要采用仿真实验的方法进行验证，所有步骤、结论都在Matlab2010上验证正确性。Below in conjunction with specific embodiment technical scheme of the present invention is further described, mainly adopt the method for simulation experiment to verify, and all steps, conclusion all verify correctness on Matlab2010.

步骤一：对成像区域任意点目标，计算目标与运动平台的距离，设置实波束扫描雷达点目标仿真参数，本发明采用如图2所示的实波束扫描雷达成像系统结构图，对应的雷达成像系统参数如表一所示。Step 1: For any point target in the imaging area, calculate the distance between the target and the moving platform, and set the real beam scanning radar point target simulation parameters. The present invention adopts the real beam scanning radar imaging system structure diagram as shown in Figure 2, and the corresponding radar imaging The system parameters are shown in Table 1.

表一Table I

参数parameter 符号symbol 数值value 载频carrier frequency f_c f _c 10GHz10GHz 带宽bandwidth BB 20MHz20MHz 发射信号时宽Transmit signal time width TT 50μs50μs 平台速度platform speed υυ 150m/s150m/s 发射信号带宽Transmit signal bandwidth BB 40MHz40MHz 平台高度platform height Hh 5Km5Km

脉冲采样频率Pulse sampling frequency PRFPRF 1000Hz1000Hz 天线扫描速度Antenna scan speed ωω 30°/s30°/s 天线波束宽度Antenna Beamwidth θθ 3°3° 扫描范围scan range ΦΦ -8°～8°-8°～8°

本实施例采用的成像场景如图3所示，途中圆点为布置与地面上的3×3的点目标，沿y轴正方向，幅度依次为1、0.9、0.8，点目标沿方位向位置分别为-4°、2°和3.5°；沿x轴方向间隔为500m，雷达平台初始时刻位置坐标为(0,0,5km)，xoy平面内目标散射函数记为f(x,y)，t时刻xoy平面内的点(x,y)与雷达平台d的距离记为R(x,y,t)。The imaging scene used in this embodiment is shown in Figure 3. The dots on the way are 3×3 point targets arranged on the ground, along the positive direction of the y-axis, the amplitudes are 1, 0.9, and 0.8 in sequence, and the position of the point target along the azimuth direction They are -4°, 2° and 3.5° respectively; the interval along the x-axis direction is 500m, the initial position coordinates of the radar platform are (0,0,5km), and the target scattering function in the xoy plane is recorded as f(x,y), The distance between the point (x, y) in the xoy plane and the radar platform d at time t is denoted as R(x, y, t).

步骤二：根据步骤一设置的成像系统参数和成像场景产生回波矩阵S(t,τ)并进行距离向FFT得到S(f_r,τ)，再根据发射信号调频斜率K和距离向参考时间τ，在频域构造距离向脉压参考函数，将S(f_r,τ)与脉压参考函数进行最大自相关运算，完成距离向脉冲压缩，脉压后的距离向频域方位向时域的二维回波数据表示为S₁(f_r,τ)，生成的回波信号如图4所示。Step 2: Generate the echo matrix S(t,τ) according to the imaging system parameters and imaging scene set in step 1, and perform range FFT to obtain S( _fr ,τ), and then according to the frequency modulation slope K of the transmitted signal and the range reference time τ, constructing the range-wise pulse pressure reference function in the frequency domain, and performing the maximum autocorrelation operation between S( _fr ,τ) and the pulse pressure reference function to complete the range-wise pulse compression, and the range-wise frequency domain azimuth direction after the pulse pressure The two-dimensional echo data of is denoted as S ₁ ( _fr ,τ), and the generated echo signal is shown in Fig. 4 .

步骤三：根据前视区域内目标的斜距距离历史R(x,y,t)的泰勒级数展开结果R(x,y,t)≈R₀-Vt，对数据S₁(f_r,τ)进行尺度变换和消除雷达平台运动造成的距离徙动，并进行距离向IFFT变换得到二维时域信号S₂(t,τ)。为了模拟存在噪声的实际情况，在数据S₂(t,τ)中加入SNR＝20dB的高斯白噪声，相应的结果如图5所示，沿方位向剖面如图6所示。Step 3: According to the Taylor series expansion result R(x,y,t)≈R ₀ -Vt of the slant distance history R(x,y,t) of the target in the forward-looking area, for the data S ₁ (f _r , τ) performs scale transformation and eliminates the range migration caused by the radar platform movement, and performs range-to-IFFT transformation to obtain a two-dimensional time-domain signal S ₂ (t,τ). In order to simulate the actual situation with noise, Gaussian white noise with SNR=20dB is added to the data S ₂ (t,τ), the corresponding results are shown in Figure 5, and the profile along the azimuth is shown in Figure 6.

步骤四：利用系统设置的扫描速度、脉冲重复时间、天线波束宽度等系统参数等生成方向向量a(θ_k)和方向矩阵A。Step 4: Generate direction vector a(θ _k ) and direction matrix A by using system parameters such as scanning speed, pulse repetition time, and antenna beam width set by the system.

步骤五：根据生成的回波信号，利用公式 $R = \frac{1}{K} Σ_{k = 1}^{K} y (k) y^{H} (k)$ 和 $g = \frac{1}{K} Σ_{k = 1}^{K} y (k)$ 分别计算协方差矩阵R和向量g，并构造维数为M×1的加权向量w_n。Step 5: According to the generated echo signal, use the formula $R = \frac{1}{K} Σ_{k = 1}^{K} the y (k) {the y}^{h} (k)$ and $g = \frac{1}{K} Σ_{k = 1}^{K} the y (k)$ Calculate the covariance matrix R and the vector g respectively, and construct a weighted vector w _n whose dimension is M×1.

步骤六：针对该距离单元第n个目标，首先，将步骤五计算出的协方差矩阵R和向量g代入到表达式中计算矩阵并将计算结果和构造的方向向量h(θ_n)代入到等式 $w_{n} = \frac{{\hat{Q}}^{- 1} h (θ_{n})}{h^{H} (θ_{n}) {\hat{Q}}^{- 1} h (θ_{n})}$ 中计算出求该目标幅度的最优加权向量w_n，将w_n的计算结果代入等式 $J (w) = w_{n}^{H} R w_{n} + {| x_{n} - w_{n}^{H} g |}^{2} - w_{n}^{H} g g^{H} w_{n}$ 中计算 ${\hat{x}}_{n} = \frac{h^{H} (θ_{n}) {\hat{Q}}^{- 1} g}{h^{H} (θ_{n}) {\hat{Q}}^{- 1} h (θ_{n})},$ 计算出该目标的幅值和定位该目标的位置，并利用该方法逐点计算出方位向各目标的幅度和位置。Step 6: For the nth target of the distance unit, first, substitute the covariance matrix R and vector g calculated in step 5 into the expression Calculate the matrix in And substitute the calculation result and the constructed direction vector h(θ _n ) into the equation $w_{no} = \frac{{\hat{Q}}^{- 1} h (θ_{no})}{h^{h} (θ_{no}) {\hat{Q}}^{- 1} h (θ_{no})}$ Calculate the optimal weight vector w _n for the target range in , and substitute the calculation result of w _n into the equation $J (w) = w_{no}^{h} R w_{no} + {| x_{no} - w_{no}^{h} g |}^{2} - w_{no}^{h} g g^{h} w_{no}$ Calculated in ${\hat{x}}_{no} = \frac{h^{h} (θ_{no}) {\hat{Q}}^{- 1} g}{h^{h} (θ_{no}) {\hat{Q}}^{- 1} h (θ_{no})},$ Calculate the amplitude of the target and locate the position of the target, and use this method to calculate the amplitude and position of each target point by point in azimuth.

最后用步骤三到步骤五的方法逐距离单元对整个扫描雷达前视作用区域的距离向进行处理，得到整个运动平台扫描雷达前视成像区域内目标二维定位结果，成像结果如图7、图8所示，图示中，三个目标的方位定位位置分别为-4°、2.045°和3.459°，定位误差分别为0°、0.045°和0.041°。从图中可以看出，本发明可以实现运动平台扫描雷达前视区域进行二维目标定位处理，可以显著提高实波束扫描雷达目标二维定位精度，定位误差低，处理结果对于目标的方位维定位、相邻目标的分辨等具有良好的改善效果。Finally, use the method from step 3 to step 5 to process the distance direction of the entire scanning radar forward-looking area by distance unit, and obtain the two-dimensional positioning results of the target in the scanning radar forward-looking imaging area of the entire moving platform. The imaging results are shown in Fig. 7 and Fig. As shown in 8, in the illustration, the azimuth positioning positions of the three targets are -4°, 2.045° and 3.459° respectively, and the positioning errors are 0°, 0.045° and 0.041° respectively. It can be seen from the figure that the present invention can realize the two-dimensional target positioning processing of the moving platform scanning radar forward-looking area, can significantly improve the two-dimensional positioning accuracy of the real beam scanning radar target, and the positioning error is low, and the processing result is accurate for the azimuth dimension positioning of the target , the resolution of adjacent targets, etc. have a good improvement effect.

本领域的普通技术人员将会意识到，这里所述的实施例是为了帮助读者理解本发明的原理，应被理解为本发明的保护范围并不局限于这样的特别陈述和实施例。本领域的普通技术人员可以根据本发明公开的这些技术启示做出各种不脱离本发明实质的其它各种具体变形和组合，这些变形和组合仍然在本发明的保护范围内。Those skilled in the art will appreciate that the embodiments described here are to help readers understand the principles of the present invention, and it should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical revelations disclosed in the present invention without departing from the essence of the present invention, and these modifications and combinations are still within the protection scope of the present invention.

Claims

1. A real beam forward-looking scanning radar target two-dimensional positioning method is characterized by comprising the following steps: the method comprises the following steps:

s1: initializing parameters of an imaging system, calculating the distance between any point target in an imaging area and a motion platform, and setting simulation parameters of the point target of the real-beam scanning radar;

s2: distance direction matching filtering is carried out;

s3: performing distance direction motion compensation processing;

s4: modeling a scanning radar azimuth echo signal;

s5: constructing a weighted least square target function;

s6: and carrying out target azimuth positioning.

2. The positioning method according to claim 1, characterized in that: the specific method for calculating the distance between the target at any point in the imaging area and the motion platform in step S1 is as follows: the zero-time position of the moving platform is recorded as (0,0, h), the moving platform moves along the y axis, the moving speed is V, the azimuth angle of the target relative to the platform is recorded as q, and the lower view angle of the radar antenna is recorded as qThe scanning speed of the radar antenna is marked as omega; then the distance between the moving platform and the target in the scene at the time t is expressed as:

wherein R is₀Is the initial distance between the motion platform and the target;

the specific method for setting the real beam scanning radar point target simulation parameters comprises the following steps: assuming that the amplitudes are all at different azimuth sampling positions at the same distance R in the scanning area, the position parameter of the target generating the motion amplitudes is set as theta (theta)₁,θ₂,...θ_N) The amplitude parameter is σ ═ (σ)₁,σ₂,...,σ_N) The radar emission signal is a chirp signal, and the echo of the scanning radar action area is recorded as S (t, tau) through coherent demodulation:

wherein tau is a distance direction time variable, rect (-) and a (-) respectively represent a distance time window and an orientation time window, K is a time frequency modulation slope of a transmitting signal, c is a light speed, and R (tau) represents a distance change between the moving platform and each target in the imaging area;

the azimuth time vector of the scanning radar imaging area is recorded as:

T_a＝[-PRI·N_a/2,-PRI·(N_a/2-1),…,PRI·(N_a/2-1)]

the distance time vector is:

T_r＝[-1/f_r·N_r/2,-1/f_r·(N_r/2-1),…,1/f_r·(N_r/2-1)]

wherein f is_rFor range-wise sampling rate, PRI is the transmit signal pulse repetition interval, N_aNumber of sampling points in azimuth, N_rThe number of distance sampling points.

3. The positioning method according to claim 2, characterized in that: the distance direction matching filtering in step S2 specifically includes the following sub-steps:

s21: distance direction pulse compression processing is carried out on the echo S (t, tau) after coherent demodulation, distance dimension target high resolution is obtained, and distance direction frequency domain and azimuth direction time domain echo signals S (f) are obtained through distance direction FFT_r,τ)：

S22: constructing a distance matching filter function H (f)_r)：

S23: h (f)_r) With echo signal S (f)_rTau) to obtain echo signals S of the distance-direction frequency domain and the azimuth-direction time domain after distance compression₁(f_r,τ)：

4. The positioning method according to claim 3, characterized in that: the distance motion compensation processing in step S3 specifically includes the following sub-steps:

s31: will be in step S1Performing Taylor expansion;

s32: neglecting the quadratic term in the expanded distance relational expression, simultaneously due to the sumIs small, socos θ ≈ 1, therefore, making R (x, y, t) ≈ R₀-Vt；

S33: structural range migration factor H (f)_r,t)：

S34: h (f)_rT) and S₁(f_rTau) multiplication is carried out to eliminate distance migration caused by radar platform movement, and distance-to-IFFT conversion is carried out to obtain two-dimensional time domain signal S with high distance positioning precision and low azimuth positioning precision₂(t,τ)：

5. The positioning method according to claim 4, characterized in that: the specific method for modeling in step S4 is as follows: for each range unit, the echo model and processing mode of azimuth scanning imaging are the same, so that the echo data of any range unit is arbitrarily selected for signal modeling, and the azimuth echo signal vector y is expressed as:

y＝A(θ)x+n

wherein,is a direction matrix composed of direction vectors corresponding to the orientation sampling points, a (n) ═ a₁，…，a_N]∈R^L×1For an antenna pattern sequence, N is the number of sampling points for one beam width, x ═ x₁，...，x_N]Representing the amplitude information of the azimuth discrete target, wherein M is the number of azimuth sampling points, and y is [ y ═ y₁，...，y_M]For the azimuth received echo signal, n is the additive noise vector.

6. The positioning method according to claim 5, characterized in that: the specific method for constructing the weighted least squares objective function in step S5 is as follows: for the nth target of the distance unit, a weighting vector w with dimension of M multiplied by 1 is constructed_nLet us orderAnd establishing a least square solution for solving a target function of the target amplitude:

where K is the number of times that the scanning radar sweeps through the target scene, x_nFor the amplitude of the nth target, the objective function is expanded to obtain:

wherein,

is a covariance matrix of the signal, order

The above equation is simplified to:

J (w) = w_{n}^{H} R w_{n} + {| x_{n} - w_{n}^{H} g |}^{2} - w_{n}^{H} g g^{H} w_{n} .

7. the positioning method according to claim 6, characterized in that: the step S6 of locating the target position specifically includes the following substeps:

s61: solving equation

J (w) = w_{n}^{H} R w_{n} + {| x_{n} - w_{n}^{H} g |}^{2} - w_{n}^{H} g g^{H} w_{n}

With respect to x_nAnd let its derivative be zero, get the derivative with respect to x_nAmplitude optimal estimation function:

{\hat{x}}_{n} = w_{n}^{H} g;

s62: will be equationSubstituting the target amplitude optimal estimation function into the formula

J (w) = w_{n}^{H} R w_{n} + {| x_{n} - w_{n}^{H} g |}^{2} - w_{n}^{H} g g^{H} w_{n}

In the middle, in an order

\hat{Q} = R - {gg}^{H},

Obtaining a reconstructed target function:

s63: calculating the objective function relation J₁(w) with respect to a weight vector w_nThe calculation method of the optimal solution comprises the following steps: calculating the objective function relation J₁(w) with respect to w_nAnd let it be zero, get the information about w_nThe optimal solution of (2):

s64: will w_nIs calculated as a result ofEntry to equation

J (w) = w_{n}^{H} R w_{n} + {| x_{n} - w_{n}^{H} g |}^{2} - w_{n}^{H} g g^{H} w_{n}

In (b), get about x_nThe amplitude of (d) is:

s65: and calculating all target amplitudes of the range cells by using the methods in the steps S63 and S64, positioning the angles of the targets, realizing the accurate positioning of the azimuth dimension of the targets, applying the algorithm to the whole scanning radar action area, processing the whole target scene by distance cells one by one, and realizing the two-dimensional accurate positioning of the targets in the imaging area.

8. The positioning method according to claim 5, characterized in that: the method for calculating the number M of the azimuth sampling points comprises the following steps:

wherein PRF is the pulse repetition frequency, ω is the scanning speed, and Φ is the scanning range.