WO2015109869A1 - 高分辨率 doa 估计方法及系统 - Google Patents

高分辨率 doa 估计方法及系统 Download PDF

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WO2015109869A1
WO2015109869A1 PCT/CN2014/088099 CN2014088099W WO2015109869A1 WO 2015109869 A1 WO2015109869 A1 WO 2015109869A1 CN 2014088099 W CN2014088099 W CN 2014088099W WO 2015109869 A1 WO2015109869 A1 WO 2015109869A1
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signal
received signal
points
maximum
receiving antenna
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French (fr)
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谢宁
郭伟斌
王晖
林晓辉
曾捷
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Shenzhen University
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Shenzhen University
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO 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
    • G01S13/00Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/06Systems determining position data of a target
    • G01S13/42Simultaneous measurement of distance and other co-ordinates
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO 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
    • G01S13/00Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/06Systems determining position data of a target
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO 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
    • G01S3/00Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic or electromagnetic waves, or particle emission, not having a directional significance, are being received
    • G01S3/02Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic or electromagnetic waves, or particle emission, not having a directional significance, are being received using radio waves
    • G01S3/74Multi-channel systems specially adapted for direction-finding, i.e. having a single antenna system capable of giving simultaneous indications of the directions of different signals

Definitions

  • the invention belongs to the field of wireless communication technologies, and in particular relates to a high-resolution DOA estimation method and system suitable for a MIMO radar system.
  • MIMO The radar uses multiple antenna techniques to simultaneously transmit independent signal beams to detect targets and receive corresponding target transmit signals.
  • the transmitted signal carries information about the target of the launch, such as angle, distance, Doppler shift, etc., which can be extracted at the receiving end by means of a matched filter.
  • MIMO The radar can flexibly adopt the high-bandwidth, two-way digital beamforming and waveform diversity techniques of the new-generation radar system, and requires each antenna to transmit mutually orthogonal signals.
  • the array elements of the antenna array are spatially separated by a certain interval and space. Targets form spatial diversity, which can improve the ability to detect air targets.
  • the characteristics of the transmitted signal in MIMO radar and the design of spatial diversity improve the resolution of the DOA estimation method.
  • the existing DOA estimation algorithms used in MIMO radar mainly include: multi-signal classification (MUSIC) method, Capon method, amplitude and phase estimation (APES) method, and maximum likelihood ratio test (GLRT) method. These algorithms can all be applied to DOA estimation in MIMO radar. To some extent (such as the number of transmitting antennas and receiving antennas is large, the number of sampling points is large) can provide relatively high DOA resolution, but these The shortcomings of the method are as follows: (1) The number of target sources that can be estimated is limited, especially in the case where the number of transmitting antennas and receiving antennas is small, the number of target sources that can be estimated depends on the transmitting array. And the number of antennas that can be shared by the receiving array.
  • the DOA estimation algorithm of the existing method can estimate the maximum number of target sources. , where M t represents the number of transmitting antennas, N r represents the number of receiving antennas; (2) When the number of transmitting antennas and receiving antennas is small, the estimation performance is unstable, the accuracy is not high enough, and the resolution capability is not strong.
  • the first technical problem to be solved by the present invention is to provide a high resolution DOA estimation method.
  • the aim is to increase the degree of freedom of the antenna without increasing the existing receiving and transmitting antennas, thereby increasing the resolution of the DOA estimation and the number of target sources that can be estimated.
  • the present invention is achieved by a high resolution DOA estimation method, the method comprising the steps of:
  • Step A Each receiving antenna receives a transmission signal reflected by the target source
  • Step B scanning the received signal of each receiving antenna by using each transmitting signal
  • Step C step B
  • the scanned signals are respectively multiplied by the transmitted signals to obtain phases corresponding to respective peak points in the received signals of each receiving antenna;
  • Step D constructing a virtual extended signal according to the phase obtained in step C and the transmitted signal;
  • Step E calculating a covariance of the new received signal by using the virtual extended signal and the original received signal to form a new received signal
  • the Capon beamforming coefficient which in turn completes the DOA estimate.
  • a second technical problem to be solved by the present invention is to provide a high resolution DOA estimation system, including:
  • a scanning module configured to scan a received signal of each receiving antenna by using each of the transmitting signals; the transmitting signal is reflected by the target source;
  • phase calculation module configured to multiply the scanned signals by the transmitted signals respectively, to obtain a phase corresponding to each peak point in the received signal of each receiving antenna
  • a virtual extended signal construction module configured to construct a virtual extended signal according to the phase obtained by the phase calculation module and the transmit signal
  • An estimation module configured to form the virtual extended signal and the received signal into a new received signal, and calculate a covariance sum of the new received signal The Capon beamforming coefficient, which in turn completes the DOA estimate.
  • the present invention makes full use of the mutual orthogonal characteristics of the transmit waveforms in the MIMO radar and the design of the spatial diversity, and performs matched filtering and recovery signals on the received signals, and then performs virtual extension of the signals. Therefore, the degree of freedom of the antenna is increased without increasing the antenna (mainly equivalent to increasing the actual number of receiving antennas), thereby improving the estimation accuracy and the number of target sources that can be estimated.
  • the number of target sources that can be estimated is greater than the limit of the original method (where M t is the number of transmit antennas and N r is the number of receive antennas).
  • FIG. 1 is a flowchart showing an implementation of a high resolution DOA estimation method provided by the present invention
  • Figure 2 is an illustration of the existing capon provided by the present invention. An implementation flow chart for selecting between the estimation method and the estimation method provided by the present invention;
  • the capon method, the actual increase antenna capon method, and the estimated angle root mean square error RMSE of the estimation method provided by the present invention are compared with the SNR;
  • the capon method, the actual increase of the antenna capon method, and the estimation method provided by the present invention are compared with the RMSE as a function of the number of target sources.
  • the transmitted signal can be expressed as:
  • T represents the period of the transmitted signal
  • I a time delay
  • Figure 1 shows the implementation flow of the high resolution DOA estimation method provided by the present invention, which is described in detail below.
  • Step A Each receiving antenna receives a transmission signal reflected by the target source.
  • the receiving antenna receives the signal, and the signal received by each receiving antenna is a row vector signal with a sampling point of L.
  • Step B scanning the received signal of each receiving antenna by using a transmitting signal.
  • the invention utilizes the characteristics of the correlation between the transmitted waveforms, and scans the received signals of each receiving antenna with the transmitted signals;
  • the received signal arriving at the receiving antenna after the target reflection can be expressed as:
  • c,f and Re represents the speed of light, the carrier frequency, and the reflection coefficient of the kth target source.
  • d k (0) represents the distance from the initial time of the kth target source to the origin
  • d mk t/r (t) represents the distance between the mth transmit/receive antenna and the kth target source.
  • n 1 (t) and n 2 (t) represent the received noise signals of the two receiving antennas, and the mean and the variance are equal.
  • the estimated error is: .
  • step B count the number N of maximum points scanned by each receiving antenna in step B, and the number of maximum points of each receiving antenna.
  • step C is performed, and when the number N of the maximum value points of the respective receiving antennas is equal and not greater than the preset maximum number of thresholds, then Using the original Capon
  • the estimation method performs an estimation of the DOA.
  • the preset threshold value of the maximum number of points is 2 .
  • Step C step B
  • the scanned signals are respectively multiplied by the transmitted signals to obtain phases corresponding to respective peak points in the received signals of each of the receiving antennas.
  • Step D Construct a virtual received signal according to the phase obtained in step C and the transmitted signal as the obtained virtual extended signal.
  • step B build the first virtual extension signal as:
  • Step E The new received signal is composed of the virtual extended signal and the original received signal, the covariance and beamforming coefficients of the new received signal are calculated, the corresponding estimated spectrum is calculated by using the obtained beamforming coefficient, and the obtained estimated spectrum is subjected to an extreme value.
  • Point search select the maximum point as the estimation result, complete Estimate of the DOA.
  • N r is the number of receiving antennas
  • T is the transposition of the matrix
  • y1m , y2m , yN r m is the first, second, and N r after being reflected by the target source at the mth pulse.
  • the estimated spectrum of the target reflection coefficient can be obtained as: (19)
  • Figure 11 shows the high resolution DOA provided by the present invention. Estimate the structural principle of the system, in which each module can be realized by software, hardware or a combination of software and hardware.
  • the high resolution DOA estimation system includes a scanning module 111 and a phase calculation module 112. , a virtual extended signal construction module 113, and an estimation module 114.
  • the scanning module 111 For scanning the received signal of each receiving antenna with each transmitted signal, the transmitted signal is reflected by the target source; then the phase calculation module 112 The scanned signals are respectively multiplied by the transmitted signals to obtain phases corresponding to respective peak points in the received signals of each of the receiving antennas.
  • Virtual extended signal construction module 113 based on phase calculation module 112 The obtained phase and the transmitted signal construct a virtual extended signal; finally, the virtual extended signal and the received signal are combined by the estimation module 114 to form a new received signal, and the covariance and Capon of the new received signal are calculated.
  • the beamforming coefficients which in turn complete the estimation of the DOA.
  • the estimation module 114 obtains a new received signal by the following formula:
  • N r is the number of receiving antennas
  • T is the transposition of the matrix
  • y1m , y2m , yN r m is the first, second, and N r after being reflected by the target source at the mth pulse.
  • the system further includes a determining module for the statistical scanning module 111 For each number N of the thresholds of the maximum number of points that are scanned by each receiving antenna, when the number of maximum points of the respective receiving antennas is equal to N and greater than the preset threshold of the maximum number of points Trigger phase calculation module 112 The calculation is performed, and when the number N of the maximum value points of the respective receiving antennas is equal and not greater than the preset threshold value of the maximum number of points, the trigger estimation module 114 uses the original Capon estimation method for DOA. Estimate. It has been verified by experiments that the preset threshold value of the maximum number of points is 2, which is more effective.
  • the invention improves the degree of freedom of the antenna without increasing the existing receiving antenna and the transmitting antenna, and is especially suitable when the number of sampling points is small and the SNR is small. High-resolution DOA estimation in MIMO radars with low or high number of sampling points.

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

一种高分辨率DOA估计方法及系统,适用于MIMO雷达技术领域。该方法包括下述步骤:各接收天线接收由目标源反射的发射信号(A);利用每个发射信号对每根接收天线的接收信号进行扫描(B);将所扫描到的信号分别与发射信号相乘,得到每根接收天线的接收信号中各个峰值点对应的相位(C);根据得到的相位以及发射信号构建虚拟接收信号作为得到的虚拟扩展信号(D);利用由所述虚拟扩展信号和原始的接收信号组成新的接收信号,计算所述新的接收信号的协方差和Capon波束形成系数,进而完成DOA的估计(E)。本方法在不增加天线的情况下,使估计精度和可以估计的目标源个数得到提高。

Description

高分辨率 DOA 估计方法及系统 Technical Field
本发明属于无线通信技术领域,尤其涉及一种适用于 MIMO 雷达系统的高分辨率 DOA 估计方法及系统。
Background Art
MIMO 雷达利用多天线技术同时发射独立的信号波束来探测目标,并接收相应的目标发射信号。发射信号中承载着有关发射目标的信息,如角度、距离、多普勒平移等等,这些信息都可以利用匹配滤波器的方法在接收端提取出来。 MIMO 雷达可以灵活采用新一代雷达系统的高带宽、双程数字波束合成和波形分集技术,同时要求各天线发射相互正交的信号,其天线阵列的各个阵元在空间分置一定的间隔,对空间目标形成空间分集,可以提高对空中目标的检测能力。 MIMO 雷达中的发射信号的特点以及空间分集的设计提高了 DOA 估计方法的分辨率。
已有的应用于 MIMO 雷达中的 DOA 估计算法主要有:多信号分类 (MUSIC) 方法、 Capon 方法、幅度和相位估计 (APES) 方法、最大似然比测试 (GLRT) 方法。这些算法本身可以都可以应用到 MIMO 雷达中的 DOA 估计,在一定程度上 ( 如发射天线和接收天线根数较多,采样点个数大的情形 ) 可以提供比较高的 DOA 分辨率,但是这些方法的缺点主要有: (1) 可以估计的目标源个数都受到一定的限制,尤其是在发射天线和接收天线根数较少的情况下,其可以估计的目标源个数依赖与发射阵列和接收阵列的可以共享的天线根数,已有方法的 DOA 估计算法可以估计的目标源个数最大值为
Figure 1402-appb-I000001
,其中 Mt 表示的发射天线根数, Nr 表示接收天线根数; (2) 算法在发射天线和接收天线根数较少时,估计性能不稳定,精度不够高,分辨率能力不强。
Technical Problem
本发明所要解决的第一个技术问题在于提供一种 高分辨率 DOA 估计方法 ,旨在不增加现有接收天线和发射天线的情况下提高天线的自由度,从而提高 DOA 估计的分辨率以及可以估计的目标源个数。
Technical Solution
本发明是这样实现的,一种 高分辨率 DOA 估计方法,所述方法包括下述步骤:
步骤 A ,各接收天线接收由目标源反射的发射信号;
步骤 B ,利用每个发射信号对每根接收天线的接收信号进行扫描;
步骤 C ,将步骤 B 所扫描到的信号分别与发射信号相乘,得到每根接收天线的接收信号中各个峰值点对应的相位;
步骤 D ,根据步骤 C 得到的相位以及发射信号构建虚拟扩展信号;
步骤 E ,利用由所述虚拟扩展信号和原始的接收信号组成新的接收信号,计算所述新的接收信号的协方差和 Capon 波束形成系数,进而完成 DOA 的估计。
本发明所要解决的第二个技术问题在于提供一种高分辨率 DOA 估计系统,包括:
扫描模块,用于利用每个发射信号对每根接收天线的接收信号进行扫描;所述发射信号由目标源反射;
相位计算模块,用于将扫描到的信号分别与发射信号相乘,得到每根接收天线的接收信号中各个峰值点对应的相位;
虚拟扩展信号构建模块,用于根据所述相位计算模块得到的相位以及发射信号构建虚拟扩展信号;
估计模块,用于将所述虚拟扩展信号和接收信号组成新的接收信号,计算所述新的接收信号的协方差和 Capon 波束形成系数,进而完成 DOA 的估计。
Advantageous Effects
本发明与现有技术相比,充分利用了 MIMO 雷达中发射波形的相互正交的特点以及空间分集的设计,对接收信号进行匹配滤波恢复信号,然后进行信号的虚拟扩展。从而在不增加天线的情况下,提高了天线的自由度 ( 主要是相当于增加了实际的接收天线根数 ) ,因此提高了估计精度和可以估计的目标源个数。可以估计的目标源个数大于原始方法的极限值
Figure 1402-appb-I000002
(其中, Mt 为发射天线根数、 Nr 为接收天线根数)。
Description of Drawings
图 1 是本发明 提供的 高分辨率 DOA 估计方法的实现流程图;
图 2 是本发明 提供的在现有的 capon 估计方法和本发明天提供的估计方法之间选择的实现流程图;
图 3A 、 3B 、 3C 是在采样点个数 L=2^7 、信噪比 SNR=0dB 的情况下,分别采用原始 capon 方法、实际增加天线 capon 方法、本发明提供的估计方法得到的 DOA 估计图;
图 4A 、 4B 、 4C 是在采样点个数 L=2^7 、信噪比 SNR=20dB 的情况下,分别采用原始 capon 方法、实际增加天线 capon 方法、本发明提供的估计方法得到的 DOA 估计图;
图 5A 、 5B 、 5C 是在采样点个数 L=2^10 、信噪比 SNR=0dB 的情况下,分别采用原始 capon 方法、实际增加天线 capon 方法、本发明提供的估计方法得到的 DOA 估计图;
图 6A 、 6B 、 6C 是在采样点个数 L=2^10 、信噪比 SNR=20dB 的情况下,分别采用原始 capon 方法、实际增加天线 capon 方法、本发明提供的估计方法得到的 DOA 估计图;
图 7A 、 7B 分别是在采样点个数 L=2^7 和采样点个数 L=2^10 的情况下,采用原始 capon 方法、实际增加天线 capon 方法、本发明提供的估计方法的估计角度均方根误差 RMSE 随 SNR 的变化比较示意图;
图 8A 、 8B 分别是在 SNR=0dB 和 SNR=20dB 的情况下,采用原始 capon 方法、实际增加天线 capon 方法、本发明提供的估计方法时 RMSE 随采样点个数的变化比较示意图;
图 9A 、 9B 分别是在采样点个数 L=2^7 和 SNR=0dB 的情况下,采用原始 capon 方法、实际增加天线 capon 方法、本发明提供的估计方法时 RMSE 随目标源个数的变化比较示意图;
图 10A 、 10B 分别是在采样点个数 L=2^10 和 SNR=0dB 的情况下,采用原始 capon 方法、实际增加天线 capon 方法、本发明提供的估计方法时 RMSE 随目标源个数的变化比较示意图。
Mode for Invention
为了使本发明的目的、技术方案及优点更加清楚明白,以下结合附图及实施例,对本发明进行进一步详细说明。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。
在 MIMO 雷达中,发射信号可以表示为:
Figure 1402-appb-C000001
(1)
其中 i={1,...,Mt} 表示发射天线数,wi 表示哈达玛矩阵的第i 列,si 表示由等概率分布 -1 和 1 组成的实数随机矩阵的第i 列, t 表示时间。 MIMO 雷达中发射波形之间相互正交且独立,因此存在:
Figure 1402-appb-C000002
(2)
其中 T 表示发射信号的周期,
Figure 1402-appb-C000003
表示时间延迟,
Figure 1402-appb-C000004
是一个很小的数值,当采样点个数 L=512 时,
Figure 1402-appb-C000005
接近 0.1 ,且随着采样点个数越大
Figure 1402-appb-C000006
越小,本发明就充分利用这一点对信号进行匹配恢复。为了说明具体步骤,下文以发射天线根数Mt=1 ,接收天线根数Nr=2 ,目标源个数 K=2为实例进行说明。
图 1 示出了本发明 提供的 高分辨率 DOA 估计方法的实现流程,详述如下。
步骤 A ,各接收天线接收由目标源反射的发射信号。
接收天线接收信号,且每根接收天线接收的信号为一个采样点为L 的行向量信号。
步骤 B ,利用发射信号对每根接收天线的接收信号进行扫描。
本发明利用发射波形之间的相关性的特点,用发射信号对每根接收天线的接收信号进行扫描;
在第 m 个脉冲,经过目标反射后到达接收天线的接收信号可以表示为:
Figure 1402-appb-C000007
(3)
Figure 1402-appb-C000008
(4)
其中c,f 和
Figure 1402-appb-C000009
分别表示光速,载波频率和第 k 个目标源的反射系数。dk(0) 表示第k 个目标源初始时刻到原点的距离,dmk t/r(t) 表示第m 个发射 / 接收天线到第k 个目标源之间的距离。n1(t) 和 n2(t) 表示 2 根接收天线的接收的噪声信号,且均值和方差相等。假设发射波形为窄带信号,目标相对移动缓慢,则接收信号中接收到的由于目标导致的延迟都相同为2dk(0)/c ,因此接收信号可以简化为:
Figure 1402-appb-C000010
(5)
Figure 1402-appb-C000011
(6)
为了简化公式 (5) 和 (6) ,做如下假设:
Figure 1402-appb-C000012
(7)
Figure 1402-appb-C000013
(8)
所有目标源的反射系数相等,即
Figure 1402-appb-C000014
。则公式 (5) 和 (6) 可以简化为:
Figure 1402-appb-C000015
(9)
Figure 1402-appb-C000016
(10)
利用信号的相关性的特点,因为
Figure 1402-appb-C000017
是一个很小的值,当采样点个数很大时这个值小于 0.1 。为了说明的方便,定义一个
Figure 1402-appb-C000018
表示发射波形和噪声之间的互相关系数,在 SNR=0dB 时,这个值接近 0.1 。充分利用上述特点,可以对
Figure 1402-appb-C000019
进行恢复:
Figure 1402-appb-C000020
(11)
Figure 1402-appb-C000021
(12)
Figure 1402-appb-C000022
(13)
Figure 1402-appb-C000023
(14)
其中估计误差为 :
Figure 1402-appb-C000024
进一步地,如图 2 所示,还包括在现有的 capon 估计方法与本发明提供的估计方法直接选择的步骤。首先统计步骤 B 中每根接收天线扫描到的极大值点的个数 N ,当各个接收天线的极大值点的个数 N 相等且大于预设的极大值点个数阈值时,执行步骤 C ,而当各个接收天线的极大值点的个数 N 相等且不大于预设的极大值点个数阈值时,则采用原始的 Capon 估计方法进行 DOA 的估计。本发明中,上述预设的极大值点个数阈值为 2 。
步骤 C ,将步骤 B 所扫描到的信号分别与发射信号相乘,得到每根接收天线的接收信号中各个峰值点对应的相位。
步骤 D ,根据步骤 C 得到的相位以及发射信号构建虚拟接收信号,作为得到的虚拟扩展信号。
利用步骤 B 中恢复出来的
Figure 1402-appb-C000025
, 构建第一个虚拟扩展信号为:
Figure 1402-appb-C000026
(15)
利用同样的方法可以得到第二个虚拟扩展信号为:
Figure 1402-appb-C000027
(16)
步骤 E ,利用由虚拟扩展信号和原始的接收信号组成新的接收信号,计算新的接收信号的协方差和波束形成系数,利用得到的波束形成系数计算对应的估计谱,对得到的估计谱进行极值点的搜索,选取其中的极大值点作为估计结果,完成 DOA 的估计。
因此,新的接收信号 r1 表示为:
Figure 1402-appb-C000028
(17)
其中, Nr 表示接收天线的根数, T 表示矩阵的转置, y1m 、 y2m , yNrm 为在第 m 个脉冲时,由目标源反射后到达第 1 根、第 2 根、第 Nr 根接收天线的接收信号,
Figure 1402-appb-C000029
为构建的虚拟扩展信号。
利用得到的新的接收信号,计算其协方差矩阵为:R=E{r1r1 H} ,则其波束形成系数为:
Figure 1402-appb-C000030
(18)
由波束形成系数,可以得到目标反射系数的估计谱为:
Figure 1402-appb-C000031
(19)
其中Rx=XTX* 。然后按照原始的 Capon 估计方法完成 DOA 的估计,不再赘述。
图 3 至图 10 从各个方面对 采用原始 capon 方法、实际增加天线 capon 方法、本发明提供的估计方法实现的 DOA 估计效果进行了对比,可以看出本发明提供的估计方法在信噪比 SNR 比较低和采样点个数比较大时,其估计性能比原始的 Capon 方法更好。
图 11 示出了本发明提供的 高分辨率 DOA 估计系统的结构原理,其中各个模块可以通过软件、硬件或软硬件结合的方式实现。
参照图 11 ,本高分辨率 DOA 估计系统包括扫描模块 111 、相位计算模块 112 、虚拟扩展信号构建模块 113 、估计模块 114 。其中,扫描模块 111 用于利用每个发射信号对每根接收天线的接收信号进行扫描,发射信号由目标源反射;然后相位计算模块 112 将扫描到的信号分别与发射信号相乘,得到每根接收天线的接收信号中各个峰值点对应的相位。虚拟扩展信号构建模块 113 根据相位计算模块 112 得到的相位以及发射信号构建虚拟扩展信号;最后,由估计模块 114 将虚拟扩展信号和接收信号组成新的接收信号,计算新的接收信号的协方差和 Capon 波束形成系数,进而完成 DOA 的估计。
其中,估计模块 114 通过如下公式得到新的接收信号:
Figure 1402-appb-C000032
其中,Nr 表示接收天线的根数, T 表示矩阵的转置, y1m 、 y2m , yNrm 为在第 m 个脉冲时,由目标源反射后到达第 1 根、第 2 根、第 Nr 根接收天线的接收信号,
Figure 1402-appb-C000033
为构建的虚拟扩展信号。
进一步地,该系统还包括一判断模块,用于 统计扫描模块 111 对每根接收天线扫描到的大于预设的极大值点个数阈值的个数 N ,当各个接收天线的极大值点的个数 N 相等且大于预设的极大值点个数阈值时,触发相位计算模块 112 执行计算,而当各个接收天线的极大值点的个数 N 相等且不大于预设的极大值点个数阈值时,触发 估计模块 114 采用原始的 Capon 估计方法进行 DOA 的估计。经试验验证,上述预设的极大值点个数阈值为 2 时效果较为理想。
上述各模块的运算原理如上文,此处不再一一赘述。
本发明在不增加现有接收天线和发射天线的情况下提高天线的自由度,尤其适用于当采样点个数比较少且 SNR 比较低或者采样点个数比较多的情况下的 MIMO 雷达中高分辨率的 DOA 估计。
以上所述仅为本发明的较佳实施例而已,并不用以限制本发明,凡在本发明的精神和原则之内所作的任何修改、等同替换和改进等,均应包含在本发明的保护范围之内。

Claims (10)

  1. 一种 高分辨率 DOA 估计方法,其特征在于,所述方法包括下述步骤:
    步骤 A ,各接收天线接收由目标源反射的发射信号;
    步骤 B ,利用每个发射信号对每根接收天线的接收信号进行扫描;
    步骤 C ,将步骤 B 所扫描到的信号分别与发射信号相乘,得到每根接收天线的接收信号中各个峰值点对应的相位;
    步骤 D ,根据步骤 C 得到的相位以及发射信号构建虚拟扩展信号;
    步骤 E ,利用所述虚拟扩展信号和接收信号组成新的接收信号,计算所述新的接收信号的协方差和 Capon 波束形成系数,进而完成 DOA 的估计。
  2. 权利要求1所述的高分辨率DOA估计方法,其特征在于,在步骤B与步骤C之间,还包括下述步骤:
    步骤B1,统计步骤B中每根接收天线扫描到的极大值点的个数N;
    步骤B2,当各个接收天线的极大值点的个数N相等且大于预设的极大值点个数阈值时,执行步骤C。
  3. 如权利要求1所述的高分辨率DOA估计方法,其特征在于,步骤E中新的接收信号r1通过如下公式得到:
    Figure 1402-appb-C000034
    其中,Nr表示接收天线的根数,T表示矩阵的转置,y1m、y2m,yNrm为在第m个脉冲时,由目标源反射后到达第1根、第2根、第Nr根接收天线的接收信号,
    Figure 1402-appb-C000035
    为构建的虚拟扩展信号。
  4. 如权利要求2所述的高分辨率DOA估计方法,其特征在于,在步骤B与步骤C之间,还包括下述步骤:
    步骤B3,当各个接收天线的极大值点的个数N相等且不大于预设的极大值点个数阈值时,则采用原始的Capon估计方法进行DOA的估计。
  5. 如权利要求2或4所述的高分辨率DOA估计方法,其特征在于,所述预设的极大值点个数阈值为2。
  6. 一种高分辨率DOA估计系统,其特征在于,包括:
    扫描模块,用于利用每个发射信号对每根接收天线的接收信号进行扫描;所述发射信号由目标源反射;
    相位计算模块,用于将扫描到的信号分别与发射信号相乘,得到每根接收天线的接收信号中各个峰值点对应的相位;
    虚拟扩展信号构建模块,用于根据所述相位计算模块得到的相位以及发射信号构建虚拟扩展信号;
    估计模块,用于将所述虚拟扩展信号和接收信号组成新的接收信号,计算所述新的接收信号的协方差和Capon波束形成系数,进而完成DOA的估计。
  7. 如权利要求6所述的系统,其特征在于,所述系统还包括:
    判断模块,用于统计所述扫描模块对每根接收天线扫描到的极大值点的个数N,当各个接收天线的极大值点的个数N相等且大于预设的极大值点个数阈值时,触发所述相位计算模块执行计算。
  8. 如权利要求6所述的系统,其特征在于,所述估计模块通过如下公式得到新的接收信号:
    Figure 1402-appb-C000034
    其中,Nr表示接收天线的根数,T表示矩阵的转置,y1m、y2m,yNrm为在第m个脉冲时,由目标源反射后到达第1根、第2根、第Nr根接收天线的接收信号,
    Figure 1402-appb-C000035
    为构建的虚拟扩展信号。
  9. 如权利要求7所述的系统,其特征在于,所述估计模块还用于在各个接收天线的极大值点的个数N相等且不大于预设的极大值点个数阈值时,采用原始的Capon估计方法进行DOA的估计。
  10. 如权利要求7或9所述的系统,其特征在于,所述预设的极大值点个数阈值为2。
PCT/CN2014/088099 2014-01-24 2014-10-03 高分辨率 doa 估计方法及系统 Ceased WO2015109869A1 (zh)

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