CN104267387A

CN104267387A - Target detection method of carrier-free ultra-wide band radar

Info

Publication number: CN104267387A
Application number: CN201410444386.5A
Authority: CN
Inventors: 张顺生; 董纪私; 高鹏
Original assignee: University of Electronic Science and Technology of China
Current assignee: University of Electronic Science and Technology of China
Priority date: 2014-09-03
Filing date: 2014-09-03
Publication date: 2015-01-07
Anticipated expiration: 2034-09-03

Abstract

The invention relates to radar target detection technology. The invention discloses a target detection method of a carrier-less ultra-wideband radar. The technical scheme mainly includes the following steps: a. performing pulse cancellation processing on the received K times scanning echo signals; The signal is processed through a sliding window for energy accumulation; c, comparing the result obtained in step b with the first threshold Th ₁ to obtain the target data point; d, judging whether there are P consecutive target data points exceeding the first threshold Th ₁ , if Then keep the first data point, then judge the subsequent data points, and so on, to obtain other data points; e, combine the data points obtained through step d and carry out Hough transform processing; f, after processing through step e The result of is compared with the second threshold Th ₂ , if it is greater than the second threshold Th ₂ , the target is detected; otherwise, the target does not exist; where Th ₂ is set by the radar parameters. The invention effectively reduces the calculation amount of the Hough transform detection method.

Description

A Target Detection Method for Carrier-Free UWB Radar

技术领域technical field

本发明涉及雷达目标检测技术，特别涉及发射信号为纳秒级无载波脉冲且目标回波形式未知情况下的检测技术。The invention relates to a radar target detection technology, in particular to a detection technology under the condition that the transmitted signal is a nanosecond-level non-carrier pulse and the form of the target echo is unknown.

背景技术Background technique

无载波超宽带雷达发射纳秒级无载波脉冲，具有高距离分辨率、低截获概率、抗干扰、强穿透力等常规雷达无法比拟的优点，尤其是优越的反隐身能力，使之成为目前研究的热点。无载波超宽带雷达的目标回波来自整个目标的各个散射中心，其回波形式是发射信号与目标冲击响应的卷积，表现为目标散射点的一维距离像，而不再像常规窄带雷达那样可以看作是发射信号的“复制品”。大多数情况下，由于目标冲击响应是未知的，因而雷达检测中常用的匹配滤波和相关检测方法不再适用于无载波超宽带雷达。Carrier-free ultra-wideband radar transmits nanosecond-level non-carrier pulses, which have advantages that conventional radars cannot match, such as high distance resolution, low probability of interception, anti-jamming, and strong penetration, especially the superior anti-stealth capability, making it the current research hotspot. The target echo of the carrier-free ultra-wideband radar comes from each scattering center of the entire target. The echo form is the convolution of the transmitted signal and the target impulse response, which is expressed as a one-dimensional range image of the target scattering point, which is no longer like a conventional narrow-band radar. That can be seen as a "replica" of the transmitted signal. In most cases, since the target impulse response is unknown, the commonly used matched filter and correlation detection methods in radar detection are no longer applicable to carrier-free UWB radars.

近年来，随着超宽带雷达技术的发展，出现了短时相关法、小波去噪法、Hough变换等多种目标检测方法，但这些检测方法都存在各自的局限性。短时相关法是通过对信号数据简单分段后进行相关处理，但由于数据段较短而受信号信噪比的制约，信噪比较小时无法保证检测效果；小波去噪法需要知道实际信号的先验信息。而且，上述两种检测方法无法应用于发射信号为纳秒级无载波脉冲且目标回波形式未知情况下的检测。Hough变换法难以解决算法运算量与检测性能之间的矛盾，在实际应用中受到限制。In recent years, with the development of ultra-wideband radar technology, many target detection methods such as short-term correlation method, wavelet denoising method, Hough transform, etc. have appeared, but these detection methods have their own limitations. The short-term correlation method is to perform correlation processing by simply segmenting the signal data, but because the data segment is short and limited by the signal-to-noise ratio, the detection effect cannot be guaranteed when the signal-to-noise ratio is small; the wavelet denoising method needs to know the actual signal prior information. Moreover, the above two detection methods cannot be applied to detection when the transmitted signal is a nanosecond-level non-carrier pulse and the form of the target echo is unknown. The Hough transform method is difficult to solve the contradiction between the calculation amount of the algorithm and the detection performance, and is limited in practical application.

发明内容Contents of the invention

本发明所要解决的技术问题，就是针对现有Hough变换检测方法，因提高检测性能而带来算法运算量增大的缺点，提出一种改进的Hough变换检测方法实现无载波超宽带雷达的目标检测，在尽可能减小目标检测性能损失的同时降低运算量。The technical problem to be solved by the present invention is to propose an improved Hough transform detection method to realize the target detection of carrierless ultra-wideband radar for the existing Hough transform detection method. , reducing the amount of computation while minimizing the loss of target detection performance.

本发明解决所述技术问题，采用的技术方案是，一种无载波超宽带雷达的目标检测方法，通过向目标发射无载波脉冲信号s(t)，并对接收的扫描回波信号进行处理检测目标信息，其特征在于，包括以下步骤：The present invention solves the technical problem by adopting a technical solution of a target detection method for a carrier-free ultra-wideband radar, by transmitting a carrier-free pulse signal s(t) to the target, and processing and detecting the received scanning echo signal The target information is characterized in that it includes the following steps:

a、对接收的K次扫描回波信号按下式进行脉冲对消处理：a. Perform pulse cancellation processing on the received K scan echo signals according to the following formula:

${s the s}_{k k}^{d d} ((n no)) = = {s the s}_{k k + + 11} ((n no)) - - {s the s}_{k k} ((n no))$

其中，K为整数，由雷达参数设定；s_k(n)为第k个回波信号的第n个距离单元的测量值；为一次对消后的结果；n＝1,2,...,N_r；N_r为距离采样点数，由雷达参数设定；Among them, K is an integer, which is set by the radar parameters; s _k (n) is the measured value of the nth distance unit of the kth echo signal; is the result after a cancellation; n=1,2,...,N _r ; N _r is the number of distance sampling points, which is set by the radar parameters;

b、对经步骤a处理后的信号通过滑窗处理进行能量积累：b. Carry out energy accumulation on the signal processed by step a through sliding window processing:

${E E.}_{k k} ((n no)) = = {Σ Σ}_{n no = = 11}^{W W} {[[{s the s}_{k k}^{d d} ((n no))]]}^{22}$

其中，E_k(n)为积累的信号能量；W为滑窗长度，由雷达参数设定；Among them, E _k (n) is the accumulated signal energy; W is the length of the sliding window, which is set by the radar parameters;

c、将E_k(n)与第一门限Th₁比较，得到目标数据点；其中，Th₁由雷达参数设定；c. Comparing E _k (n) with the first threshold Th ₁ to obtain the target data point; wherein, Th ₁ is set by the radar parameters;

d、判断超过第一门限Th₁的目标数据点是否连续出现P个，若是则保留第一个数据点，然后判断后续的数据点，以此类推，得到其他数据点；其中，P为正整数，由雷达参数设定；d. Judging whether there are P consecutive target data points exceeding the first threshold _Th1 , if so, keep the first data point, then judge the subsequent data points, and so on, to obtain other data points; wherein, P is a positive integer , set by the radar parameters;

e、对经步骤d得到的数据点进行组合并进行Hough变换处理；E, combining the data points obtained through step d and performing Hough transform processing;

f、将经步骤e处理后的结果与第二门限Th₂进行比较，若大于第二门限Th₂，则检测到目标；反之，则目标不存在；其中，Th₂由雷达参数设定。f. Compare the result processed in step e with the second threshold Th ₂ , if it is greater than the second threshold Th ₂ , the target is detected; otherwise, the target does not exist; wherein, Th ₂ is set by the radar parameters.

具体的，所述脉冲信号s(t)为高斯脉冲信号，具有如下表达式：Specifically, the pulse signal s(t) is a Gaussian pulse signal with the following expression:

$s the s ((t t)) = = {αe αe}^{{- - a a}^{22} {t t}^{22}}$

其中，a为脉宽因子且T为脉冲持续时间；α为脉冲幅度；a、T、α由雷达参数设定。where a is the pulse width factor and T is the pulse duration; α is the pulse amplitude; a, T, α are set by the radar parameters.

具体的，所述步骤e中数据点组合为D_a：Specifically, the combination of data points in step e is D _a :

${D D.}_{a a} = = [\begin{matrix} 11 & 11 & . . . . . . & 11 & . . . . . . & k k & . . . . . . & k k & . . . . . . & K K - - 11 \\ {n no}_{{l l}_{11}} & {n no}_{{l l}_{22}} & . . . . . . & {n no}_{{l l}_{j j}} & . . . . . . & {n no}_{{k k}_{11}} & . . . . . . & {n no}_{{k k}_{j j}} & . . . . . . & {n no}_{{((K K - - 11))}_{j j}} \end{matrix}]$

其中，k表示第k次扫描，k∈[1,K]；表示第k次扫描中第j个超过第一门限的数据点所在的距离单元。Among them, k represents the kth scan, k∈[1,K]; Indicates the distance unit where the jth data point exceeding the first threshold in the kth scan is located.

具体的，所述步骤e中Hough变换的具体方法为：Concretely, the specific method of Hough transform in the described step e is:

ρ＝xcosθ+ysinθ θ∈[0,π]ρ=xcosθ+ysinθ θ∈[0,π]

其中，ρ、θ为数据点极坐标，分别表示距离和角度参数；x、y为数据点的直角坐标。Among them, ρ and θ are the polar coordinates of the data points, representing distance and angle parameters respectively; x and y are the rectangular coordinates of the data points.

本发明的有益效果是，在检测性能没有明显下降的条件下，有效降低了Hough变换检测方法的运算量，一定程度克服了传统Hough变换检测方法运算量与检测性能之间矛盾，特别适合一些特定场合的应用。The beneficial effect of the present invention is that, under the condition that the detection performance does not decrease significantly, the calculation amount of the Hough transform detection method is effectively reduced, and the contradiction between the calculation amount and the detection performance of the traditional Hough transform detection method is overcome to a certain extent, and it is especially suitable for some specific occasional application.

附图说明Description of drawings

图1为目标模型示意图；Figure 1 is a schematic diagram of the target model;

图2为实施例的数据点采集示意图；Fig. 2 is the data point acquisition schematic diagram of embodiment;

图3为本发明与传统Hough变换方法的检测性能曲线。Fig. 3 is the detection performance curve of the present invention and the traditional Hough transform method.

具体实施方式Detailed ways

下面结合附图及实施例详细描述本发明的技术方案。需要说明的是，实施例中的参数并不影响本发明的一般性。The technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings and embodiments. It should be noted that the parameters in the examples do not affect the generality of the present invention.

实施例Example

本例无载波超宽带雷达系统，发射信号为无载波高斯脉冲信号s(t)，具有如下形式：In this example, the carrier-free UWB radar system transmits a carrier-free Gaussian pulse signal s(t), which has the following form:

$s the s ((t t)) = = {αe αe}^{- - {a a}^{22} {t t}^{22}}$

其中a为脉宽因子且T为脉冲持续时间，α为幅度。a、T、α由雷达参数设定。where a is the pulse width factor and T is the pulse duration, and α is the amplitude. a, T, α are set by radar parameters.

根据瞬态电磁场理论，表面使用吸波材料或外形比较复杂的目标，其各个散射中心都可以看作是一个色散通道。其目标冲激响应为h(t)：According to the transient electromagnetic field theory, each scattering center of a target using absorbing materials or a complex shape on the surface can be regarded as a dispersion channel. Its target impulse response is h(t):

$h h ((t t)) = = {Σ Σ}_{m m = = 11}^{M m} {A A}_{m m} {e e}^{j j {φ φ}_{m m}} exp exp [[- - {a a}_{m m}^{22} {((t t - - {τ τ}_{m m}))}^{22}]]$

其中，a_m为第m个散射中心响应函数的脉宽因子，与a的定义相同，M表示目标散射中心的个数，A_m和τ_m分别表示第m个散射中心所对应的幅度以及该散射中心与雷达径向距离所对应的时延，φ_m为相位因子。Among them, a _m is the pulse width factor of the response function of the mth scattering center, which is the same as the definition of a, M represents the number of target scattering centers, A _m and τ _m represent the amplitude corresponding to the mth scattering center and the The time delay corresponding to the radial distance between the scattering center and the radar, φ _m is the phase factor.

那么，无载波超宽带雷达的目标回波为发射信号与目标冲激响应的卷积，对应的回波信号为r(t)：Then, the target echo of the carrier-free UWB radar is the convolution of the transmitted signal and the target impulse response, and the corresponding echo signal is r(t):

r(t)＝s(t)*h(t)r(t)=s(t)*h(t)

其中，*表示卷积。Among them, * means convolution.

根据上述信号模型，使用matlab(一种计算机算法语言)可以产生如图1所示目标模型的回波信号。仿真的具体参数如下：According to the above signal model, using matlab (a computer algorithm language) can generate the echo signal of the target model as shown in Fig. 1 . The specific parameters of the simulation are as follows:

雷达参数设置：脉冲持续时间T＝1ns；脉冲幅度α＝1；采样频率f_s＝5GHz；脉冲重复频率PRF＝550Hz；扫描回波次数K＝20；距离采样点数N_r＝600；滑窗积累的滑窗长度W＝15；第一门限对应的虚警概率为0.1；第二门限对应的虚警概率(总虚警概率)为10^-4；P＝4；Hough变换采用的距离和角度参数空间划分的二维网格大小分别为：M_ρ＝800，M_θ＝800；接收的目标回波的信杂比范围为-15dB～0dB。Radar parameter settings: pulse duration T = 1ns; pulse amplitude α = 1; sampling frequency f _s = 5GHz; pulse repetition frequency PRF = 550Hz; number of scanning echoes K = 20; distance sampling points N _r = 600; sliding window accumulation The sliding window length W=15; the false alarm probability corresponding to the first threshold is 0.1; the false alarm probability (total false alarm probability) corresponding to the second threshold is 10 ^-4 ; P=4; the distance and angle parameters used by Hough transform The two-dimensional grid sizes for space division are: M _ρ =800, M _θ =800; the signal-to-clutter ratio of the received target echo ranges from -15dB to 0dB.

目标参数设置：如图1所示，从左到右包含9个散射中心，每个散射中心的幅度相同，相位均匀分布，对应的时延分别为1ns，6ns，6ns，6ns，6ns，7ns，7ns，10ns，10ns。目标以100m/s的径向速度飞行。Target parameter setting: As shown in Figure 1, there are 9 scattering centers from left to right. Each scattering center has the same amplitude and uniform phase distribution. The corresponding time delays are 1ns, 6ns, 6ns, 6ns, 6ns, 7ns, 7ns, 10ns, 10ns. The target flies at a radial velocity of 100m/s.

具体检测过程如下：The specific detection process is as follows:

A.对接收的20次扫描回波信号s_k(n)进行脉冲对消处理，以抑制杂波对目标回波的干扰。经对消处理后的信号为 A. Perform pulse cancellation processing on the received 20 scanning echo signals s _k (n) to suppress the interference of clutter to the target echo. The signal after cancellation processing is

其中，k＝1,2,...,19，n＝1,2,...,600。Wherein, k=1,2,...,19, n=1,2,...,600.

B.对每一个脉冲对消后的数据通过滑窗处理进行能量积累，以提高目标回波的信杂噪比。经滑窗积累后的信号能量为E_k(n)：B. Data after each pulse cancellation Energy accumulation is carried out through sliding window processing to improve the signal-to-noise ratio of the target echo. The signal energy accumulated by the sliding window is E _k (n):

其中W＝15。where W=15.

C.将滑窗处理后的信号E_k(n)与第一门限Th₁进行比较，以剔除目标幅度较小的数据点。其中，第一门限Th₁由下式确定：C. Comparing the signal E _k (n) processed by the sliding window with the first threshold Th ₁ to eliminate data points with smaller target amplitudes. Wherein, the first threshold _Th1 is determined by the following formula:

${P P}_{{f f}_{11}} = = P P (({E E.}_{k k} ((n no)) > > {Th Th}_{11}))$

式中为第一门限对应的虚警概率，这里为0.1。设第k次信号E_k(n)超过门限的数据点有M_k个，则通过第一门限检测后形成的目标数据点集合为如图2中数据点1～4、6、8、11～18……。In the formula is the false alarm probability corresponding to the first threshold, which is 0.1 here. Assuming that there are M _k data points for the kth signal E _k (n) exceeding the threshold, then the target data point set formed after passing the first threshold detection is Data points 1~4, 6, 8, 11~18... as shown in Figure 2.

D.判断超过第一门限的目标数据点是否连续出现4个，若是则保留第一个数据点，循环处理该步骤直到k＝K-1。得到数据点A、N、R……，分别对应数据点1、11、15……，如图2所示。这样处理可以有效减低后续Hough变换检测的运算量。通过该步骤减小数据量处理，得到新的目标数据点集合为如图2中A、N、R……数据点。D. Judging target data points exceeding the first threshold Whether there are 4 in a row, if so, keep the first data point, and process this step in a loop until k=K-1. Data points A, N, R... are obtained, corresponding to data points 1, 11, 15..., as shown in Figure 2. Such processing can effectively reduce the computation load of the subsequent Hough transform detection. Through this step to reduce the amount of data processing, the new target data point set is obtained as As shown in Figure 2, A, N, R... data points.

E.对新的目标数据点集合进行组合，得到直角坐标系下的数据点集合Da：E. Set of new target data points Combining to get the data point set Da in the Cartesian coordinate system:

然后，对直角坐标系下的数据点集合D_a进行Hough变换处理：Then, perform Hough transform processing on the data point set D _a in the Cartesian coordinate system:

E1)划分距离和角度两维网格：将(ρ,θ)平面划分为两维网格，沿ρ轴划分的网格个数为800，沿θ轴划分的网格个数为800。那么，ρ轴每个网格的长度为其中(x_max,y_max)为目标在x轴和y轴的最大坐标；θ轴每个网格的长度为θ∈[0,π]。这样，得到转换矩阵H为E1) Divide distance and angle two-dimensional grids: divide the (ρ, θ) plane into two-dimensional grids, the number of grids divided along the ρ axis is 800, and the number of grids divided along the θ axis is 800. Then, the length of each grid on the ρ axis is Where (x _max , y _max ) is the maximum coordinate of the target on the x-axis and y-axis; the length of each grid on the θ axis is θ∈[0,π]. In this way, the conversion matrix H is obtained as

$H h = = [\begin{matrix} cos cos {θ θ}_{11} & sin sin {θ θ}_{11} \\ {cos cos θ θ}_{22} & sin sin {θ θ}_{22} \\ . . . . . . & . . . . . . \\ cos cos {θ θ}_{800800} & sin sin {θ θ}_{800800} \end{matrix}]$

其中△θ＝θ_i+1-θ_i。Where Δθ=θ _i+1 −θ _i .

E2)数据映射：将直角坐标系下的数据点集合D_a通过转换矩阵H映射到(ρ,θ)空间，则有E2) Data mapping: map the data point set D _a in the Cartesian coordinate system to the (ρ, θ) space through the transformation matrix H, then there is

其中，Num为D_a中数据点个数，即经步骤d后得到的数据点个数。Among them, Num is the number of data points in D _a , that is, the number of data points obtained after step d.

E3)计算矩阵R中元素的数值：定义矩阵R，并初始化为零矩阵E3) Calculate the value of the elements in the matrix R: define the matrix R and initialize it to a zero matrix

其中，M_θ＝800，M_ρ＝800。设矩阵V中某个元素ρ_ij(i＝1,...,800；j＝1,...,Num)落在ρ轴的第q个网格上，则可知其对应曲线上的点落在(ρ,θ)空间的第(i,q)个网格上。这样，将矩阵R中对应元素r_iq(i＝1,...,800；q＝1,...,800)加1。Among them, M _θ =800, M _ρ =800. Assuming that an element ρ _ij (i=1,...,800; j=1,...,Num) in the matrix V falls on the qth grid of the ρ axis, we can know the point on the corresponding curve Falls on the (i,q)th grid in (ρ,θ) space. In this way, 1 is added to the corresponding element r _iq (i=1,...,800; q=1,...,800) in the matrix R.

F.将经Hough处理后得到的矩阵R中的所有元素与第二门限Th₂进行比较，若大于门限，则检测到目标；反之，则目标不存在。其中，Th₂由下式确定：F. Comparing all the elements in the matrix R obtained after Hough processing with the second threshold Th ₂ , if it is greater than the threshold, the target is detected; otherwise, the target does not exist. Wherein, _Th2 is determined by the following formula:

${P P}_{{f f}_{22}} = = P P (({r r}_{iq iq} > > {Th Th}_{22}))$

式中为总虚警概率，为10^-4。In the formula is the total false alarm probability, which is 10 ^-4 .

为验证本发明的检测性能，采用蒙特卡洛仿真的方法对不同信杂噪比下的检测性能进行统计。设蒙特卡洛仿真的次数为500，总虚警概率为10^-4，检测性能曲线如图3所示，从图3中可以看出：与传统Hough变换方法相比，本发明仅在信杂比约-12dB～-8dB时检测概率略有下降，其他情况下则没有明显区别。In order to verify the detection performance of the present invention, a Monte Carlo simulation method is used to make statistics on the detection performance under different signal-to-noise ratios. Assuming that the number of Monte Carlo simulations is 500 and the total false alarm probability is 10 ^-4 , the detection performance curve is shown in Fig. 3. It can be seen from Fig. 3 that: compared with the traditional Hough transform method, the present invention is only effective in signal The detection probability decreases slightly when the ratio is about -12dB～-8dB, but there is no obvious difference in other cases.

为进一步验证本发明的运算效率，将本发明与传统Hough变换方法所占用的CPU时间进行对比(CPU为Intel(R)Core(TM)2 Quad CPU Q6600，主频为2.4GHZ，内存为8G)。这些算法所占用的时间是通过1000次求平均处理得到的，如表1所示。从表1中可以看出：本发明的运算效率有较大提高，是传统Hough变换方法的4倍。For further verifying the computing efficiency of the present invention, the CPU time taken by the present invention and traditional Hough transformation method is compared (CPU is Intel (R) Core (TM) 2 Quad CPU Q6600, main frequency is 2.4GHZ, internal memory is 8G) . The time taken by these algorithms is obtained by averaging 1000 times, as shown in Table 1. It can be seen from Table 1 that the computing efficiency of the present invention is greatly improved, which is 4 times that of the traditional Hough transform method.

表1Table 1

传统Hough变换traditional Hough transform 本发明(P＝4)Hough变换The present invention (P=4) Hough transform CPU时间(s)CPU time(s) 32.0132.01 7.917.91

Claims

1. a target detection method of a carrier-free ultra-wideband radar, by transmitting a carrier-free pulse signal s (t) to the target, and processing the detection target information to the scanning echo signal received, it is characterized in that, comprising the following steps:

a. Perform pulse cancellation processing on the received K scan echo signals according to the following formula:

{s the s}_{k k}^{d d} ((n no)) = = {s the s}_{k k + + 11} ((n no)) - - {s the s}_{k k} ((n no))

Among them, K is an integer, which is set by the radar parameters; s _k (n) is the measured value of the nth distance unit of the kth echo signal; is the result after a cancellation; n=1,2,...,N _r ; N _r is the number of distance sampling points, which is set by the radar parameters;

b. Carry out energy accumulation on the signal processed in step a through sliding window processing:

{E E.}_{k k} ((n no)) = = {Σ Σ}_{n no = = 11}^{W W} {[[{s the s}_{k k}^{d d} ((n no))]]}^{22}

Among them, E _k (n) is the accumulated signal energy; W is the length of the sliding window, which is set by the radar parameters;

c. Comparing E _k (n) with the first threshold Th ₁ to obtain the target data point; wherein, Th ₁ is set by the radar parameters;

d. Judging whether there are P consecutive target data points exceeding the first threshold _Th1 , if so, keep the first data point, then judge the subsequent data points, and so on, to obtain other data points; wherein, P is a positive integer , set by the radar parameters;

E, combining the data points obtained through step d and performing Hough transform processing;

f. Compare the result processed in step e with the second threshold Th ₂ , if it is greater than the second threshold Th ₂ , the target is detected; otherwise, the target does not exist; wherein, Th ₂ is set by the radar parameters.

2. the target detection method of a kind of carrierless ultra-wideband radar according to claim 1, is characterized in that, described pulse signal s (t) is Gaussian pulse signal, has following expression:

s the s ((t t)) = = α α {e e}^{- - {a a}^{22} {t t}^{22}}

where a is the pulse width factor and T is the pulse duration; α is the pulse amplitude; a, T, α are set by the radar parameters.

3. the target detection method of a kind of carrierless ultra-wideband radar according to claim 1, is characterized in that, in the described step e, data point combination is D _a :

{D D.}_{a a} = = [\begin{matrix} 11 & 11 & . . . . . . & 11 & . . . . . . & k k & . . . . . . & k k & . . . . . . & K K - - 11 \\ {n no}_{{l l}_{11}} & {n no}_{{l l}_{22}} & . . . . . . & {n no}_{{l l}_{j j}} & . . . . . . & {n no}_{{k k}_{11}} & . . . . . . & {n no}_{{k k}_{j j}} & . . . . . . & {n no}_{{((K K - - 11))}_{j j}} \end{matrix}]

Among them, k represents the kth scan, k∈[1,K]; Indicates the distance unit where the jth data point exceeding the first threshold in the kth scan is located.

4. the target detection method of a kind of carrierless ultra-wideband radar according to claim 1, is characterized in that, the concrete method of Hough transform among the described step e is:

ρ=xcosθ+ysinθ θ∈[0,π]

Among them, ρ and θ are the polar coordinates of the data points, representing distance and angle parameters respectively; x and y are the rectangular coordinates of the data points.