Monopulse forward-looking imaging algorithm based on Levenberg–Marquardt optimisation

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.

Keywords

• angular measurement
• computational complexity
• maximum likelihood estimation
• target tracking
• measurement errors
• direction-of-arrival estimation
• radar imaging
• imaging algorithm
• levenberg–marquardt optimisation
• precise angle measurement
• traditional monopulse techniques
• exact angle information
• single target
• multiple targets
• novel monopulse
• maximum likelihood estimation problem
• lm optimisation
• ml-lm
• arrival estimation
• unresolved targets
• forward-looking radar beam
• imaging framework
• angle measurement error
• angle interval adaptability