A multimodal radar varies its bandwidth (and hence resolution) based on the arrangement of target scattering features, possibly leaving unused bandwidth for other applications. In this paper, we explore bandwidth sharing scenarios between radar and communications. We divide the surveillance space into sectors and use fuzzy logic to arrive at priorities for each sector. Multi-objective optimization is used to arrive at solutions making the best use of available bandwidth between radar and communications. We also consider the problem of scheduling between tracking and surveillance for the multimodal radar. Smart scheduling is necessary to make the best use of available radar resources. We look at algorithms for special target scenarios. Tracking is performed using the particle filter algorithm.
This paper describes the underlying methodology behind an adaptive multimodal radar sensor that is capable of progressively optimizing its range resolution depending upon the target scattering features. It consists of a test-bed that enables the generation of linear frequency modulated waveforms of various bandwidths. This paper discusses a theoretical approach to optimizing the bandwidth used by the multimodal radar. It also discusses the various experimental results obtained from measurement. The resolution predicted from theory agrees quite well with that obtained from experiments for different target arrangements.
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