Abstract
We develop and present a radar waveform design method that optimizes the spectral shape of the radar waveform so that joint performance of a cooperative radar communications system is maximized. The continuous water-filling (WF) spectral-mask shaping method presented in this paper is based on the previously derived spectral-mask shaping technique. However, the method presented in this paper is modified to utilize the continuous spectral water-filling algorithm to improve communications performance. We also introduce additional practical system constraints on the autocorrelation peak side-lobe-to-main-lobe ratio and radar waveform spectral leakage. Finally, we perform a numerical study to compare the performance of the continuous WF spectral-mask-shaping method with the previously derived method. The global estimation rate, which also accounts for non-local estimation errors, and the data rate capture radar and communications performance respectively.
Highlights
Spectral congestion, caused when too many communications users concurrently attempt to access spectral resources, has quickly emerged as a serious issue for the telecommunications sector [1].A potential solution to this spectral congestion problem is to share spectral resources between radar and communications systems
We present the continuous WF spectral-mask-shaping method which parametrizes the shape of the radar waveform, and optimizes the parameters to maximize joint radar communications performance
We presented the continuous WF spectral-mask shaping radar waveform design technique which maximizes the performance of a cooperative spectrum sharing radar communications system
Summary
Spectral congestion, caused when too many communications users concurrently attempt to access spectral resources, has quickly emerged as a serious issue for the telecommunications sector [1].A potential solution to this spectral congestion problem is to share spectral resources between radar and communications systems. Research has been done into radar waveform design in the presence of signal-dependent noise to maximize various other detection and information theoretic metrics such as the mutual information, and Kullback–Liebler divergence [30,31]. Cognitive radar is another emrging technology that researchers have begun to look at as a solution to the spectral scarcity problem via radar scheduling [32] or employing cognitive radio spectrum sensing techniques, emitter localization, and power allocation to avoid interference [33,34,35,36].
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