A Waveform Design Method for Multiple-Input and Multiple-Output Radar

Abstract

A multiple-input-multiple-output radar waveform design method belongs to the radar communication technical field, and aims to provide a design method with lower related sidelobe and frequency spectrum inhibition depth, high efficiency, less consumption, high robustness, and excellent time frequency anti-interference performance; the method comprises the following steps: pre-evaluating an autocorrelation sidelobe inhibition fuzzy region according to a relative position between a strong scatterer and a to be measured object in a radar scene, thus forming a corresponding object function; analyzing MIMO radar waveform orthogonality constraint so as to form the object function satisfying the orthogonality constraint; pre-evaluating a frequency domain interference fuzzy frequency band zone according to scene prior information, thus forming the corresponding object function; forming a constant modulus phase coding waveform constrained condition; forming a loose alternative projection algorithm framework; solving a waveform design according to the loose alternative projection algorithm framework, thus providing three waveform optimization output modes. The loose alternative projection constant modulus waveform coding design enables the MIMO radar to have batter detection performance.

Description

technical field [0001] The invention belongs to the technical field of radar communication, and in particular relates to a radar waveform design method for MIMO radar to meet the task requirements of time domain and frequency domain. Background technique [0002] Today's military or civilian requirements make radar mission scenarios increasingly complex. In order to cope with complex and changing scenes, radar adaptability is particularly important. Among them, waveform diversity can be regarded as a manifestation of adaptability and has become a hot research topic (see literature: Cognitive radar: a way of the future, Haykin S.; Signal Processing Magazine, IEEE, 2006, 23(1): 30 -40; Adaptive radar phase-coded waveform design, J.D. Zhang, X.H. Zhu, H.Q. Wang; Electron. Lett.2009, 45(20) 1052-1053; Spatial diversity in radars-models and detection performance, Eran, F., Alexander, H., & Rick, S.B.; IEEE Transactions on Signal Processing, 2006, 54(3), 823-838). Whether it is...

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Problems solved by technology

However, the algorithm takes too long and the related side lobe level amplitude is poor, so it is difficult to meet the requirements of engineering practice.

However, it provides a lot of inspiration for follow-up research. The improved cyclic algorithm framework based on alternating projections has achieved more obvious effects than the CAN algorithm family (see literature: phase encoding waveform design in zero autocorrelation zone, Li Fengcong, Zhao Yinan, Xiaolin Qiao; Acta Electronica Sinica, 2013, 12:2499-2502; Alternating Projection Coding Waveform Design Based on Rank-deficient Fourier Transform, Zhao Yinan, Li Fengcong, Wang Jun, Qiao Xiaolin; Acta Electronics Sinica, 2014, 06:1216-1219; Computational design of optimal wavesforms for MIMO radar via multi-dimensional iterative spectral approximation, Zhao Y N, Li F C, Zhang T; Multidm syst sign process, 11045-01400288-1, 2014); but the algorithm initialization leads to poor solution stability for non-convex problems

In addition, use the genetic algorithm to design the orthogonal waveform of MIMO radar (see literature: Polyphase orthogonal code design for MIMOradar systems, Liu B, He Z, Zeng J; 2006 CIE international conference on radar, 2006: 1-4) ; but in the late stage of iterative optimization, the algorithm often has poor population diversity, which leads to stagnation of local optimal solutions, and the scale of the algorithm also becomes a factor that limits its efficiency

However, for actual MIMO radar scenarios, such algorithms may take too long and are difficult to converge

Using sequential quadratic programming and weighted iterative methods to solve waveform design problems, the search mechanism of weight step size is difficult to adapt; this kind of algorithm based on gradient matrix has high computational complexity in the case of multi-array elements, and high-order matrix singularity may occur It is difficult to converge (see literature: A space-time joint optimization MIMO radar waveform design method, Wang Xu, Zhou Shenghua, Liu Hongwei, Bao Zheng; Xidian University Journal, 2014, 03:41-48)

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