Monopulse forward-looking imaging algorithm based on Levenberg–Marquardt optimisation
| Autor: | Tao Zhou, Bo Pang, Dahai Dai, Hao Wu, Xuesong Wang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
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 Engineering (General). Civil engineering (General) TA1-2040 |
| Zdroj: | The Journal of Engineering (2019) |
| Druh dokumentu: | article |
| ISSN: | 2051-3305 |
| DOI: | 10.1049/joe.2019.0149 |
| Popis: | 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. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
|
Plný text