Aggregation techniques for DOA estimation of radar signals
Date
2020
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Mulinde, R.
Kaushik, M.
Attygalle, M.
Aziz, S.M.
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This is a supplementary report submitted in fulfilment of Deliverable D4 of phase 3 of the collaborative research project conducted by the University of South Australia (UniSA) and the RF Systems Group of the Cyber and Electronic Warfare Division of the Defence Science and Technology (DST) group. It builds on and extends the methods and results presented in previous reports (Deliverables D2 and D4 of Phase 3). Previous reports have comprehensively investigated the estimation performance of channelized MUltiple SIgnal Classiffication (MUSIC) using both synthetic and experimentaldata. This report analyses the performance of two incoherent aggregation techniques for direction of arrival (DOA) estimation of linear frequency modulated (LFM) radar signals. The aim is to determine suitable aggregation techniques for blind DOA estimation for real-time implementation. The first technique combines the spatial pseudospectra calculated from the spatial co-variance matrix (SCM) of the signal present in each of the frequency bins obtained after frequency channelization. The second technique directly combines the spatial covariance matrices (SCMs) from each of the frequency bins before calculating a single pseudospectrum. First, we compare the DOA estimation performance of incoherent SCM-based aggregation with incoherent spatial pseudospectra-based aggregation. Secondly, we determine the types of signals and conditions for which these incoherent aggregation techniques are suitable. Finally, we demonstrate that the low-complexity SCM-based aggregation technique can achieve relatively good estimation performance under certain conditions. The two incoherent aggregation techniques discussed, thus offer a computationally efficient way in comparison to coherent processing techniques.
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Copyright 2020 The Authors