High Speed Multi-target Parameter Estimation for FA-OFDM Radar Based on Ransac Algorithm

Yinghui QUAN; Xia GAO; Minghui SHA; Wen FANG; Yachao LI; Mengdao XING

doi:10.11999/JEIT200529

Volume 43 Issue 7

Jul. 2021

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Yinghui QUAN, Xia GAO, Minghui SHA, Wen FANG, Yachao LI, Mengdao XING. High Speed Multi-target Parameter Estimation for FA-OFDM Radar Based on Ransac Algorithm[J]. Journal of Electronics & Information Technology, 2021, 43(7): 1970-1977. doi: 10.11999/JEIT200529

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Yinghui QUAN, Xia GAO, Minghui SHA, Wen FANG, Yachao LI, Mengdao XING. High Speed Multi-target Parameter Estimation for FA-OFDM Radar Based on Ransac Algorithm[J]. Journal of Electronics & Information Technology, 2021, 43(7): 1970-1977. doi: 10.11999/JEIT200529

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High Speed Multi-target Parameter Estimation for FA-OFDM Radar Based on Ransac Algorithm

doi: 10.11999/JEIT200529 cstr: 32379.14.JEIT200529

1.
School of Electronic Engineering, Xidian University, Xi’an 710071, China
2.
Beijing Institute of Radio Measurement, Beijing 100854, China
3.
National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China

Funds: The National Natural Science Foundation of China (61303035, 61772397), The Foundation Research Funds for Central University, The Innovation Fund of Xidian University

Received Date: 2020-06-29
Rev Recd Date: 2020-12-06

Available Online: 2020-12-15

Publish Date: 2021-07-10

Abstract

Abstract

In modern radar electronic battlefield, target detection and parameter estimation have great significance. Therefore, a high-speed multi-target parameter estimation method for Frequency Agile-Orthogonal Frequency Division Multiplexing (FA-OFDM) radar based on Random sampling consensus (Ransac) algorithm is proposed in this paper. Firstly, multiple narrowband OFDM subcarriers with random frequency hopping are simultaneously transmitted in each pulse of conventional frequency agile radar. The echo signals of all subcarriers in a single pulse are compressed, and then the high-resolution range of the target is synthesized by Iterative Adaptive Approach (IAA) algorithm. Furthermore, the echoes of each pulse are compressed and iterative adaptive spectrum estimated, and the high-resolution distance of different pulse time is obtained to form the observation data set. Then, according to the steps of the Ransac algorithm to estimate the signal parameter model, multiple time-distance lines are fitted, and then parameters of multiple high-speed moving targets are estimated at the same time. Finally, the influence of the Signal-to-Noise Ratio (SNR) on detection probability and the target velocity on relative error of estimation are analyzed, respectively. Simulations are provided to verify the effectiveness of the proposal.

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References(21)

References

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