Variable Doppler Starting Point Keystone Transform for Radar Maneuvering Target Detection

被引:0
作者
Jia, Wei [1 ]
Feng, Yuan [1 ]
Qiao, Xingshuai [2 ]
Wang, Tianrun [1 ]
Shan, Tao [1 ]
机构
[1] Beijing Inst Technol, Sch Informat & Elect, Beijing Key Lab Fract Signals & Syst, Beijing 100081, Peoples R China
[2] Beijing Univ Posts & Telecommun, Sch Elect Engn, Beijing 100876, Peoples R China
基金
中国国家自然科学基金;
关键词
maneuvering target detection; range migration (RM); keystone transform (KT); sinc interpolation; variable Doppler starting point keystone transform (VDSPKT); RADON-FOURIER TRANSFORM; PARAMETER-ESTIMATION; ESTIMATION ALGORITHM; INTEGRATION METHOD;
D O I
10.3390/rs16122129
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Doppler band compensated by the keystone transform (KT) is limited. Therefore, it needs to be used in conjunction with the Doppler ambiguity compensation function to correct the range migration (RM) caused by maneuvering targets with Doppler ambiguity. However, the KT implemented by sinc interpolation suffers from significant performance loss at boundaries of compensation Doppler bands. Additionally, in a multi-target scenario, KT implementation methods occupy high complexity when the Doppler range of targets spans over two compensation Doppler bands. To address the aforementioned issues, this study presents a variable Doppler starting point keystone transform (VDSPKT) method, where a new form of ambiguity compensation function is constructed, turning the Doppler starting point of the compensation band in KT variable. Firstly, the position of the compensation Doppler band is changed from fixed to adjustable as needed, enhancing the flexibility of KT. Crucially, the connection points of the compensation Doppler bands in sinc interpolation are reset, avoiding performance loss at their boundaries. Also, the compensation band is adjusted to cover the narrow Doppler frequency range caused by targets, significantly improving computational efficiency. Finally, the simulation and real data experiments demonstrate that the proposed approach effectively addresses the performance degradation and high computational complexity of KT in the aforementioned scenarios, resulting in a computational load reduced by approximately 50% compared to traditional methods.
引用
收藏
页数:21
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