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基于跳频信号的无源双基地雷达长时间相干积累方法

Long-Time Coherent Integration Method for Passive Bistatic Radar Using Frequency Hopping Signals.

作者信息

Chen Gang, Biao Xiaowei, Jin Yi, Xu Changzhi, Ping Yifan, Wang Sujun

机构信息

China Academy of Space Technology, Xi'an 710100, China.

出版信息

Sensors (Basel). 2024 Sep 26;24(19):6236. doi: 10.3390/s24196236.

Abstract

Long-time coherent integration using frequency hopping signals is a challenging problem for passive bistatic radar due to its frequency hopping characteristics. Apart from range walk, range curve, and Doppler frequency migration, Doppler diffusion caused by frequency hopping characteristics occurs within the observation time, which also lowers the detection performance. To deal with this problem, a novel coherent integration method for frequency hopping signals based on passive bistatic radar is proposed in this paper. In this novel method, range curve and range walk are eliminated by applying generalized Keystone transform. Then, Doppler frequency migration caused by the target's acceleration is compensated for by a parameter search with a designed search scope. Finally, Doppler frequency migration caused by frequency hopping characteristics is compensated for by designing a new acceleration compensation function and a revised rotation factor for Fourier transform. Since migration effects caused by frequency hopping characteristics are considered and compensated for when using frequency hopping signals, the weak target echo can be better integrated in the observation time compared to when using the existing methods. The simulation results and performance analysis illustrate the effectiveness of the proposed method.

摘要

对于无源双基地雷达而言,由于跳频信号的跳频特性,长时间相干积累是一个具有挑战性的问题。除了距离走动、距离曲线和多普勒频率迁移外,跳频特性引起的多普勒扩散在观测时间内也会出现,这也会降低检测性能。为了解决这个问题,本文提出了一种基于无源双基地雷达的跳频信号相干积累新方法。在这种新方法中,通过应用广义Keystone变换消除距离曲线和距离走动。然后,通过在设计的搜索范围内进行参数搜索来补偿目标加速度引起的多普勒频率迁移。最后,通过设计新的加速度补偿函数和修正的傅里叶变换旋转因子来补偿跳频特性引起的多普勒频率迁移。由于在使用跳频信号时考虑并补偿了跳频特性引起的迁移效应,与使用现有方法相比,弱目标回波在观测时间内能够得到更好的积累。仿真结果和性能分析表明了该方法的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/38e0/11478646/76be2b138ac0/sensors-24-06236-g001.jpg

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