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Content Provider | IET Digital Library |
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Author | Zhou, Tao Pang, Bo Dai, Dahai Wu, Hao Wang, Xuesong |
Abstract | With precise angle measurement, traditional monopulse techniques for forward-looking imaging can acquire exact angle information of one single target within a radar beam. However, when multiple targets exist in a beam, it is difficult to resolve them. To address this problem, a novel monopulse forward-looking imaging algorithm based on Levenberg–Marquardt (LM) optimisation is proposed. The core idea of this algorithm is to solve maximum likelihood estimation problem based on LM optimisation (ML-LM) to obtain the direction of arrival (DOA) estimation of unresolved targets. First, the echo model of two targets within a forward-looking radar beam is established, then the imaging framework of the proposed algorithm is introduced. Finally, the advantages of ML-LM are illustrated based on a series of evaluation criterion, including angle measurement error for various values of signal-to-noise ratio (SNR), angle interval adaptability and computational efficiency. The simulation results show that two targets within a forward-looking radar beam can be resolved and relocated accurately utilising the proposed algorithm. Meanwhile, the comparison with other algorithms shows it has higher DOA estimation accuracy, less computational complexity and a wider range of angle interval adaptability. |
Starting Page | 6593 |
Ending Page | 6597 |
Page Count | 5 |
Volume Number | 2019 |
e-ISSN | 20513305 |
Issue Number | Issue 20, Oct (2019) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/joe/2019/20 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0149 |
Journal | The Journal of Engineering |
Publisher | The Institution of Engineering and Technology |
Publisher Date | 2019-07-10 |
Access Restriction | Open |
Rights License | Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) |
Subject Keyword | Angle Interval Adaptability Angle Measurement Error Angular Measurement Arrival Estimation Computational Complexity Computer Vision And Image Processing Technique Direction of Arrival Estimation Exact Angle Information Forward-looking Radar Beam Imaging Algorithm Imaging Framework Interpolation And Function Approximation Levenberg–Marquardt Optimisation LM Optimisation Maximum Likelihood Estimation Maximum Likelihood Estimation Problem Measurement Error ML-LM Multiple Targets Novel Monopulse Numerical Analysis Optical, Image And Video Signal Processing Precise Angle Measurement Radar Equipment Radar Imaging Signal Processing And Detection Single Target Spatial Variables Measurement Statistics System And Application Target Tracking Traditional Monopulse Technique Unresolved Targets |
Content Type | Text |
Resource Type | Article |
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