WO2022151708A1 - 一种基于信号代理的多目标恒虚警率检测方法 - Google Patents

一种基于信号代理的多目标恒虚警率检测方法 Download PDF

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WO2022151708A1
WO2022151708A1 PCT/CN2021/109105 CN2021109105W WO2022151708A1 WO 2022151708 A1 WO2022151708 A1 WO 2022151708A1 CN 2021109105 W CN2021109105 W CN 2021109105W WO 2022151708 A1 WO2022151708 A1 WO 2022151708A1
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target
signal
false alarm
sample
matrix
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宋春毅
曹智辉
李俊杰
宋钰莹
徐志伟
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浙江大学
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/40—Means for monitoring or calibrating
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/35—Details of non-pulse systems
    • G01S7/352—Receivers
    • G01S7/354—Extracting wanted echo-signals
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B29/00—Checking or monitoring of signalling or alarm systems; Prevention or correction of operating errors, e.g. preventing unauthorised operation
    • G08B29/02—Monitoring continuously signalling or alarm systems
    • G08B29/04—Monitoring of the detection circuits
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/414—Discriminating targets with respect to background clutter

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  • the invention belongs to the technical field of frequency modulated continuous wave (Frequency Modulated Continuous Wave, FMCW) radar multi-target constant false alarm rate (Constant False Alarm Rate, hereinafter referred to as CFAR) detection technology, and in particular relates to a signal agent-based multi-target CFAR detection method.
  • FMCW Frequency Modulated Continuous Wave
  • CFAR Constant False Alarm Rate
  • the CFAR detection method can make the FMCW radar system have stable target detection performance, and at the same time avoid the failure of the radar receiver caused by the excessive false alarm rate.
  • most of the existing CFAR detection methods are limited by the estimation of the target-clutter environment background level. In the case of multiple targets, the interference target leads to inaccurate background level estimation, and the radar target detection performance decreases accordingly. Therefore, research on CFAR detection methods in multi-target scenarios has attracted extensive attention.
  • the traditional CFAR detection method mainly determines the detection threshold through the estimation of the environmental background level, but the multi-target shading effect caused by the interfering targets in the reference unit affects the accurate estimation of the background level, which leads to the degradation of the detection performance of the radar system.
  • the improved detection method truncates the abnormal data of the signal samples before the background level estimation, which can effectively improve the detection performance of the radar in the multi-target scene.
  • target detection still relies on the detection threshold determined by the pre-background level estimation, which cannot directly avoid the influence of interfering targets.
  • the purpose of the present invention is to aim at the deficiencies of the prior art, to provide a multi-target constant false alarm rate detection method based on signal agent, which does not need to rely on the detection threshold determined by the pre-estimated background level during multi-target detection, and can Detect objects quickly and accurately.
  • the specific technical solutions are as follows:
  • a multi-target constant false alarm rate detection method based on signal agent comprises the following steps:
  • S3 Use the target set ⁇ to truncate the original background sample x, model it strictly according to the truncated distribution, and determine the value of the proportional parameter ⁇ through maximum likelihood estimation; set the expected false alarm probability P FA , and calculate the false alarm probability P FA .
  • the alarm adjustment threshold T fa according to the calculated false alarm adjustment threshold, the signal lower than T fa in the target set ⁇ is eliminated, and the detection result is output.
  • the determination of the signal agent r in the S1 is specifically carried out in the following manner:
  • the determination of the target set ⁇ in the S2 is specifically carried out in the following manner:
  • S2.3 Select the first ⁇ largest elements in the signal agent r to obtain the target set ⁇ , which is used as the output of the signal agent detector to distinguish the clutter and the target signal.
  • step S3.1 Apply the target set ⁇ output in step S2 to the original background sample x, and remove the corresponding data to obtain a truncated version of the reduced sample
  • the multi-target constant false alarm rate detection method based on the signal agent of the present invention, the multi-target detection method of the focused FMCW radar, and the new detection algorithm are used to realize target detection without relying on the detection threshold determined by the pre-estimated environmental background level, and are comprehensive and effective. to overcome the multi-target shadowing effect.
  • FIG. 1 is a schematic diagram of a multi-object scene according to a preferred embodiment of the present invention.
  • FIG. 2 is a schematic flowchart of a multi-target constant false alarm rate detection method based on a signal agent.
  • FIG. 3 is a performance comparison diagram of the method of the present invention, the upper bound performance and the existing CFAR detection method.
  • the multi-target constant false alarm rate detection method based on the signal agent provided by the invention can effectively solve the problem of the detection performance degradation of the radar system caused by the interference target in the multi-target environment, and at the same time realize the constant false alarm adjustment threshold through the self-adaptive false alarm. the false alarm rate.
  • the millimeter-wave radar is used as the target detection sensor, and the operating frequency band is in the range of 76-81GHZ.
  • the radar system applies the multi-target constant false alarm rate detection method based on signal agent, and ten have the same size.
  • the radar reflector as the target. After the electromagnetic waves sent by the millimeter-wave radar are reflected by targets at different distances in the scene, the echo signals are received by the radar.
  • the IF signal of the radar obtains a linear measurement y in S1 and calculates the signal proxy r, both of which are complex vectors of length 1024. Then in S2, the target index ⁇ with the smallest correlation is determined to be 17, and the output target index set ⁇ is [42; 43; 48; 49; 50; 51; 76; 77; 78; 80; 81; 82; 94; 97; 114; 119; 129].
  • the adaptive false alarm adjustment threshold T fa is determined to be 2.2653 ⁇ 10 4 , and then the targets below the adjustment threshold are eliminated, and the final output detection results are [42, 50, 73, 76, 81, 94, 97, 114, 119, 129].
  • Figure 3 compares the radar receiver operating characteristic (ROC) curves of each detection method in this test scenario, and the results show that the method of the present invention is better than the existing CFAR detection method, and is closest to the upper bound performance. This shows that the CFAR detection method in the present invention can effectively overcome the multi-target occlusion effect, and has robust detection performance in multi-target scenes.
  • ROC radar receiver operating characteristic

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
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  • Computer Security & Cryptography (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

一种基于信号代理的多目标恒虚警率检测方法，属于雷达恒虚警率检测技术领域。该方法通过利用雷达信号的线性测量和感知矩阵的相关性来区分目标和杂波，然后将检测到的目标从原始背景样本中剔除得到缩减样本。最后针对缩减样本进行背景水平估计得到虚警调节门限，将低于门限的目标剔除以得到最终的恒虚警率检测结果。该方法能够自适应信号的稀疏度，不需要依赖预先估计的环境背景水平来实现目标检测，有效克服了多目标遮蔽效应。

Description

一种基于信号代理的多目标恒虚警率检测方法 技术领域
本发明属于调频连续波(Frequency Modulated Continuous Wave,FMCW)雷达多目标恒虚警率(Constant False Alarm Rate,以下简称CFAR)检测技术领域，尤其涉及一种基于信号代理的多目标CFAR检测方法。
背景技术
CFAR检测方法能使FMCW雷达系统具有稳定的目标检测性能，同时避免过高的虚警率引起雷达接收机故障。但现有的CFAR检测方法多数受制于目标-杂波环境背景水平的估计。多目标情况下，干扰目标导致不准确的背景水平估计，雷达目标检测性能随之下降。因此，多目标场景下的CFAR检测方法研究引起了广泛的关注。
在多目标场景中存在干扰目标的情况时，精确计算检测阈值是非常困难的。传统的CFAR检测方法主要通过环境背景水平估计来确定检测阈值，但参考单元中的干扰目标引起的多目标遮蔽效应影响背景水平的准确估计，从而导致雷达系统检测性能的下降。
针对传统CFAR检测方法的缺点，改进的检测方法在背景水平估计前对信号样本进行异常数据的截断处理，能有效改善雷达在多目标场景下的检测性能。但目标检测仍依赖于预先背景水平估计确定的检测门限，无法直接避免干扰目标的影响。
发明内容
本发明的目的在于针对现有技术的不足，提供一种基于信号代理的多目标恒虚警率检测方法，该方法在多目标检测时不需要依赖预先估计的背景水平确定的检测阈值，并且能够快速准确地检测目标。具体技术方案如下：
一种基于信号代理的多目标恒虚警率检测方法，该方法包括以下步骤：
S1：输入待检测的中频信号s，利用感知矩阵A获取所述待检测的中频信号的线性测量y，y＝As，求解信号代理r，r＝A *y；
S2：找到具有最低相关度的目标对应的索引λ，输出目标集合Λ；
S3：利用目标集合Λ对原背景样本x作截断处理，并严格按照截断分布对其建模，通过最大似然估计确定比例参数σ的值；设定期望的虚警概率P FA，计算得到虚警调节门限T fa；根据计算得到的虚警调节门限剔除目标集合Λ中低于T fa的信号，输出检测结果。
进一步地，所述S1中信号代理r的确定具体按照以下方式进行：
S1.1：将输入的待检测的中频信号s与所述感知矩阵A进行矩阵相乘，
Figure PCTCN2021109105-appb-000001
N为信号长度，实现待检测的中频信号的线性测量y＝As，其中，感知矩阵A选用随机高斯测量矩阵，A＝(a 1，a 2，...，a N)；
S1.2：求出线性测量y关于感知矩阵A的信号代理r，r＝A *y，所述信号代理反映了目标或杂波的能量强弱。
进一步地，所述S2中目标集合Λ的确定具体按照以下方式进行：
S2.1：对信号代理降序排列，得到
Figure PCTCN2021109105-appb-000002
j＝1，2，...，N，d为降序标记；
S2.2：确定具有最小相关度的目标索引
Figure PCTCN2021109105-appb-000003
其中，
Figure PCTCN2021109105-appb-000004
||·|| p代表
Figure PCTCN2021109105-appb-000005
范数即
Figure PCTCN2021109105-appb-000006
S2.3：在信号代理r中选取前λ个最大元素得到目标集合Λ，作为信号代理检测器的输出，以区分杂波和目标信号。
进一步地，所述S3中比例参数σ和虚警调节门限T fa的确定具体按照以下方式进行：
S3.1：将步骤S2输出的目标集合Λ应用于原背景样本x中，剔除对应数据得到截断版本的缩减样本
Figure PCTCN2021109105-appb-000007
S3.2：将缩减样本以截断的瑞利分布
Figure PCTCN2021109105-appb-000008
建模，满足
Figure PCTCN2021109105-appb-000009
其中α表示截断深度；
S3.3：根据缩减样本的截断分布的概率密度函数，确定似然函数
Figure PCTCN2021109105-appb-000010
Figure PCTCN2021109105-appb-000011
通过最大似然估计令
Figure PCTCN2021109105-appb-000012
计算出尺度参数
Figure PCTCN2021109105-appb-000013
的估计值：
Figure PCTCN2021109105-appb-000014
S3.4：根据期望的虚警概率P FA与X的累积分布函数F X(·)的关系，得到方程
Figure PCTCN2021109105-appb-000015
S3.5：根据方程(2)和(3)计算出虚警调节门限T fa
Figure PCTCN2021109105-appb-000016
本发明的有益效果如下：
本发明的基于信号代理的多目标恒虚警率检测方法，聚焦FMCW雷达多目标检测方法， 通过利用新的检测算法，不需依赖预先估计环境背景水平确定的检测阈值来实现目标检测，全面有效的克服了多目标遮蔽效应。
附图说明
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要的使用的附图作简单地介绍。
图1是本发明优选实施例的多目标场景示意图。
图2是基于信号代理的多目标恒虚警率检测方法的流程示意图。
图3是本发明方法与上界性能以及现有CFAR检测方法的性能对比图。
具体实施方式
下面根据附图和优选实施例详细描述本发明，本发明的目的和效果将变得更加明白，应当理解，此处所描述的具体实施例仅仅用以解释本发明，并不用于限定本发明。
本发明提供的基于信号代理的多目标恒虚警率检测方法，在多目标环境下能够有效解决干扰目标引起的雷达系统检测性能下降的问题，同时通过自适应的虚警调节门限，来实现恒定的虚警率。
如图1所示，多目标场景中，毫米波雷达作为目标检测传感器，工作频段在76-81GHZ范围，雷达系统应用了基于信号代理的多目标恒虚警率检测方法，十个具有相同的尺寸的雷达反射器作为目标。毫米波雷达发送的电磁波经过场景中不同距离的目标反射后，回波信号被雷达接收。
如图2所示，雷达的中频信号在S1中获取线性测量y并计算信号代理r，二者均为长度为1024的复数向量。随后在S2中确定具有最小相关度的目标索引λ为17，并输出目标索引集合Λ为[42；43；48；49；50；51；76；77；78；80；81；82；94；97；114；119；129]。最后在S3中获取缩减样本
Figure PCTCN2021109105-appb-000017
并确定自适应虚警调节门限T fa为2.2653×10 4，之后将低于调节门限的目标剔除，最后输出检测结果为[42,50,73,76,81,94,97,114,119,129]。
图3为本测试场景中各检测方法的雷达接收机操作特性(Receiver Operating Characteristic,ROC)曲线对比，结果显示本发明方法优于现有的CFAR检测方法，与上界性能最接近。这表明本发明中的CFAR检测方法能够有效的克服多目标遮蔽效应，在多目标场景中具有鲁棒的检测性能。
本领域普通技术人员可以理解，以上所述仅为发明的优选实例而已，并不用于限制发明，尽管参照前述实例对发明进行了详细的说明，对于本领域的技术人员来说，其依然可以对前 述各实例记载的技术方案进行修改，或者对其中部分技术特征进行等同替换。凡在发明的精神和原则之内，所做的修改、等同替换等均应包含在发明的保护范围之内。

Claims (2)

  1. 一种基于信号代理的多目标恒虚警率检测方法，其特征在于，该方法包括以下步骤：
    S1：输入待检测的中频信号s，利用感知矩阵A获取所述待检测的中频信号的线性测量y，y＝As，求解信号代理r，r＝A *y；
    S2：找到具有最低相关度的目标对应的索引λ，输出目标集合Λ，具体按照以下方式进行：
    S2.1：对信号代理降序排列，得到
    Figure PCTCN2021109105-appb-100001
    j＝1，2，...，N，d为降序标记，N为信号长度；
    S2.2：确定具有最小相关度的目标索引
    Figure PCTCN2021109105-appb-100002
    其中，n 1＝1/N，
    Figure PCTCN2021109105-appb-100003
    ||·|| p代表l p范数即
    Figure PCTCN2021109105-appb-100004
    S2.3：在信号代理r中选取前λ个最大元素得到目标集合Λ，作为信号代理检测器的输出，以区分杂波和目标信号；
    S3：利用目标集合Λ对原背景样本x作截断处理，并严格按照截断分布对其建模，通过最大似然估计确定比例参数σ的值；设定期望的虚警概率P FA，计算得到虚警调节门限T fa；根据计算得到的虚警调节门限剔除目标集合Λ中低于T fa的信号，输出检测结果；
    所述比例参数σ和虚警调节门限T fa的确定具体按照以下方式进行：
    S3.1：将步骤S2输出的目标集合Λ应用于原背景样本x中，剔除对应数据得到截断版本的缩减样本
    Figure PCTCN2021109105-appb-100005
    S3.2：将缩减样本以截断的瑞利分布
    Figure PCTCN2021109105-appb-100006
    建模，满足
    Figure PCTCN2021109105-appb-100007
    其中α表示截断深度；
    S3.3：根据缩减样本的截断分布的概率密度函数，确定似然函数
    Figure PCTCN2021109105-appb-100008
    Figure PCTCN2021109105-appb-100009
    通过最大似然估计令
    Figure PCTCN2021109105-appb-100010
    计算出尺度参数
    Figure PCTCN2021109105-appb-100011
    的估计值：
    Figure PCTCN2021109105-appb-100012
    S3.4：根据期望的虚警概率P FA与X的累积分布函数F X(·)的关系，得到方程
    Figure PCTCN2021109105-appb-100013
    S3.5：根据方程(2)和(3)计算出虚警调节门限T fa
    Figure PCTCN2021109105-appb-100014
  2. 根据权利要求1所述的基于信号代理的多目标恒虚警率检测方法，其特征在于，所述S1中信号代理r的确定具体按照以下方式进行：
    S1.1：将输入的待检测的中频信号s与所述感知矩阵A进行矩阵相乘，
    Figure PCTCN2021109105-appb-100015
    实现待检测的中频信号的线性测量y＝As，其中，感知矩阵A选用随机高斯测量矩阵，A＝(a 1，a 2，...，a N)；
    S1.2：求出线性测量y关于感知矩阵A的信号代理r，r＝A *y，所述信号代理反映了目标或杂波的能量强弱。
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