Evolutionary multi-objective optimisation of the pulse burst waveform in solid-state VHF moving target detection radar

被引:0
作者
Jevtic, Milos [1 ,2 ]
Zogovic, Nikola [2 ]
Graovac, Stevica [1 ]
机构
[1] Univ Belgrade, Sch Elect Engn, Bulevar Kralja Aleksandra 73, Belgrade, Serbia
[2] Univ Belgrade, Inst Mihailo Pupin, Volgina 15, Belgrade, Serbia
关键词
Doppler radar; radar detection; search radar; object detection; evolutionary computation; radar tracking; radar signal processing; Pareto optimisation; search problems; complex pulse burst waveform; blind Doppler intervals; range eclipsing; multiple pulse repetition frequencies; waveform design; multiobjective optimisation problem; mathematical model; waveform optimisation problem; exact Pareto optimal set; exhaustive search; objective functions; multiobjective evolutionary algorithm; online waveform adaptation; evolutionary multiobjective optimisation; high frequency band; performance evaluation test; PO set; solid-state VHF band moving target detection air surveillance radar; very high frequency band; APERTURE;
D O I
10.1049/iet-rsn.2019.0033
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A solid-state, very high frequency (VHF) band, moving target detection air surveillance radar requires a complex pulse burst waveform to mitigate the visibility issues originating from the blind Doppler intervals and range eclipsing. The waveform employs multiple pulse repetition frequencies to mitigate the effects of the blind Doppler intervals and interleaves short and long pulses to mitigate range eclipsing. In the authors' previous works, they pointed out that the waveform design is a multi-objective optimisation problem and defined the mathematical model of the waveform optimisation problem. They also presented how the exact Pareto optimal (PO) set can be determined by means of exhaustive search. In this paper, they improve the mathematical model of the waveform optimisation problem by altering the way in which one of the objective functions is calculated and adding a new constraint, which eliminates meaningless solutions. Finally, they propose a solution method based on a multi-objective evolutionary algorithm. The performance evaluation test indicates that compared to the exhaustive search, the proposed method provides a solution that is insignificantly different. However, the proposed method is more scalable and requires over three orders of magnitude smaller number of comparisons to determine the PO set, which makes it more viable for the online waveform adaptation.
引用
收藏
页码:2093 / 2101
页数:9
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