Radar maneuvering target detection and motion parameter estimation based on TRT-SGRFT

2017 ◽  
Vol 133 ◽  
pp. 107-116 ◽  
Author(s):  
Xiaolong Li ◽  
Guolong Cui ◽  
Wei Yi ◽  
Lingjiang Kong
Keyword(s):  
Parameter Estimation ◽  
Target Detection ◽  
Motion Parameter ◽  
Maneuvering Target ◽  
Motion Parameter Estimation

Approach for space‐based radar manoeuvring target detection and high‐order motion parameter estimation

2015 ◽  
Vol 9 (6) ◽  
pp. 732-741 ◽  
Author(s):  
Penghui Huang ◽  
Guisheng Liao ◽  
Zhiwei Yang ◽  
Yuxiang Shu ◽  
Wentao Du
Keyword(s):  
Parameter Estimation ◽  
Target Detection ◽  
High Order ◽  
Motion Parameter ◽  
Motion Parameter Estimation

scholarly journals An Efficient Method for Ground Maneuvering Target Refocusing and Motion Parameter Estimation Based on DPT–KT–MFP

2021 ◽  
Vol 13 (6) ◽  
pp. 1092
Author(s):  
Mingming Tian ◽  
Guisheng Liao ◽  
Shengqi Zhu ◽  
Xiongpeng He ◽  
Yongjun Liu ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Doppler Frequency ◽  
Real Data ◽  
Motion Parameter ◽  
Doppler Spectrum ◽  
Matched Filtering ◽  
Cubic Phase ◽  
Maneuvering Target ◽  
Motion Parameter Estimation ◽  
Quadratic Phase

The image of ground maneuvering targets may be defocused due to the Doppler ambiguity, high-order range migration (RM), and Doppler frequency migration (DFM) caused by the target’s complex motions in a synthetic aperture radar (SAR) system. To settle these problems, an efficient algorithm based on discrete polynomial-phase transform (DPT), keystone transform (KT), and matched filtering processing (MFP) is presented for ground maneuvering target refocusing and motion parameter estimation in this paper. Firstly, the DPT is applied to transform the cubic phase into the quadratic phase and simultaneously eliminate the quadratic RM, cubic RM, and quadratic DFM. Furthermore, the Doppler ambiguity containing Doppler center blur and Doppler spectrum ambiguity is also dealt with effectively by introducing a very small fixed lay time after DPT operation. Then, the KT is performed to correct the linear RM. After that, the matched filtering function related to the target’s equivalent third-order coefficient is constructed to compensate for the residual linear DFM in the range-time and slow-time domain. Lastly, a well-refocused image of the maneuvering target can be acquired, and the target’s motion parameters can be estimated effectively. The proposed algorithm has high computational efficiency and possesses favorable refocusing performance and motion parameter estimation precision. Simulation and real data processing results prove the effectiveness of the presented algorithm.

Sign in / Sign up

Export Citation Format

Share Document