Monopulse forward‐looking imaging algorithm based on Levenberg–Marquardt optimisation
Tao Yun Zhou, Bo Pang, Dahai Dai, Hao Wu, Xuesong Wang · The Journal of Engineering · 2019
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.