Open AccessOptimised radar waveform design based on the relative entropy constraint
Author(s) -
Xiao Yu,
Hu XiaoXiang
Publication year - 2023
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
eISSN - 1751-9683
pISSN - 1751-9675
DOI - 10.1049/sil2.12169
Subject(s) - waveform , kullback–leibler divergence , false alarm , computer science , entropy (arrow of time) , principle of maximum entropy , algorithm , radar , performance metric , mimo , constraint (computer aided design) , metric (unit) , eigenvalues and eigenvectors , upper and lower bounds , mathematics , artificial intelligence , telecommunications , physics , engineering , mathematical analysis , channel (broadcasting) , geometry , management , operations management , quantum mechanics , economics
A new strategy to optimise the waveform of multiple‐input multiple‐output (MIMO) radar under the relative entropy constraint and signal‐to‐noise ratio (SNR) constraint is presented. The Kullback–Leibler divergence (KLD) is exploited between the two probability density functions of binary hypothesis testing as the design metric. A particular analysis of detection performance is made here to illuminate the balance between the false alarm and missing alarm probabilities. The results of the simulation demonstrate that the waveform design process constrained by relative entropy outperforms the process employing an explicit SNR constraint when the SNR is relatively low (i.e., within the interval [−2 dB, 0.5 dB]). The enhanced performance is attributable to the capability of the proposed optimisation process to focus the energy of the transmission waveform onto components where the eigenvalues of the target signal are large and the eigenvalues of the noise are small.