基于多帧回波的微弱目标检测算法研究

发布时间：2018-01-11 08:16

本文关键词：基于多帧回波的微弱目标检测算法研究　出处：《西安电子科技大学》2014年硕士论文　论文类型：学位论文

【摘要】：近年来,随着目标RCS的进一步减小,微弱目标检测问题已经成为雷达技术领域中的重点和难点,能否实时发现空间中的微弱目标对提高现代雷达的战斗力至关重要。微弱目标的回波信号由于具有极其低的信噪比,传统的雷达信号处理方法往往不能实现对此类目标的理想检测和跟踪。通过增加积累时间可以有效提高微弱目标的信噪比,因此连续长时间的积累是目前微弱目标检测领域的一个研究热点。然而对传统的机械扫描雷达来说,对目标的连续长时间积累通常无法实现,只能利用雷达在多个扫描周期得到的连续多帧回波信号。本文从非起伏目标的回波信号模型出发,重点研究了基于多帧回波信号的微弱目标检测算法,主要的研究内容如下:1.回顾了雷达信号处理的基本概念和方法。详细介绍了线性调频信号、脉冲压缩等基础概念,重点分析了相参积累和非相参积累的特点,并通过计算机仿真实验对两种信号积累方式的性能进行了验证和比较。然后详细介绍了两种常用的TBD算法,并给出了相应的计算机仿真实验的结果。2.针对TBD算法在多帧回波信号间进行非相参积累导致的能量损失问题,研究了多帧回波信号的相参积累算法。在详细分析了运动目标多帧回波信号模型的基础上,提出了三种多帧回波相参积累算法:基于包络插值移位的相参积累算法、基于频域校正的相参积累算法和基于Keystone变换的相参积累算法,并通过计算机仿真实验对其性能进行了验证和比较。3.基于本文所研究的多帧回波检测算法,对某型号雷达的实测数据进行了分析和处理,包括对单帧回波信号的相参积累、多帧回波信号的TBD处理、多帧回波信号的相参积累处理。详细分析了影响多帧回波信号相参积累性能的因素,提出了相应的解决方法并给出了计算机仿真实验的结果。最后本文提出了一种新的基于空间慢时间的多帧回波相参积累算法,并使用该算法进行了计算机仿真和实测数据处理。
[Abstract]:In recent years, with the further reduction of target RCS, weak target detection has become the focus and difficulty in the field of radar technology. It is very important to find weak targets in space in real time to improve the combat effectiveness of modern radar. The echo signals of weak targets have extremely low signal-to-noise ratio (SNR). The traditional radar signal processing method often can not achieve the ideal detection and tracking of such targets, and can effectively improve the SNR of weak targets by increasing the accumulation time. Therefore, the accumulation of continuous long time is a hot topic in the field of weak target detection. However, for the traditional mechanical scanning radar, the continuous long time accumulation of the target is usually unable to achieve. We can only use the continuous multi-frame echo signal obtained by radar in multiple scanning periods. Based on the echo signal model of non-undulating target, the weak target detection algorithm based on multi-frame echo signal is studied in this paper. The main research contents are as follows: 1. The basic concepts and methods of radar signal processing are reviewed. The basic concepts of linear frequency modulation signal and pulse compression are introduced in detail. The characteristics of coherent accumulation and non-coherent accumulation are analyzed, and the performance of the two signal accumulation methods is verified and compared by computer simulation experiments. Then, two commonly used TBD algorithms are introduced in detail. The results of the corresponding computer simulation experiments are given. 2. The energy loss caused by the non-coherent accumulation of the TBD algorithm between the multi-frame echo signals is given. 2. The coherent accumulation algorithm of multi-frame echo signal is studied, and the model of multi-frame echo signal of moving object is analyzed in detail. Three kinds of coherent integration algorithms are proposed: one based on envelope interpolation shift, one based on frequency domain correction, and the other is based on Keystone transform. The performance of the radar is verified and compared by computer simulation experiments. Based on the multi-frame echo detection algorithm studied in this paper, the measured data of a certain type of radar are analyzed and processed. Including the coherent accumulation of single echo signal, the TBD processing of multi-frame echo signal and the coherent accumulation processing of multi-frame echo signal. The factors influencing the coherent accumulation performance of multi-frame echo signal are analyzed in detail. The corresponding solutions are proposed and the results of the computer simulation experiments are given. Finally, a new algorithm based on spatial slow time coherent integration of multi-frame echo is proposed in this paper. The algorithm is used for computer simulation and data processing.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN911.23

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