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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 39007 (05)
- University: Sharif University of Technology
- Department: Electrical Engineering
- Advisor(s): Behnia, Fereidoon
- Abstract:
- Waveform design for Target identification and classification in MIMO radar systems has been studied in several recent works. While the previous works considered signal independent noise and found optimal signals for an estimation algorithm, here we extend the results to the case where clutter is also present and then we will find the optimum waveform for several estimators differing in the assumptions on the given statistics. Several different approaches to the optimal waveform design are proposed, including minimizing the error of MMSE estimator, minimizing the maximum error of the covariance shaping least square (CSLS) estimator and minimizing the MSE error of scaled least square (SLS) estimator. Choosing optimal waveform for MMSE estimator leads to the Semi-definite programming (SDP) problem, a convex optimization problem which can be efficiently solved through numerical methods. Explicit solution is developed for this SDP problem in two cases. In the first case, target and clutter covariance matrices are jointly diagonalizable and in the second one, signal to noise ratio (SNR) is sufficiently high. Finding the optimal transmit signals for CSLS estimator results in a minimax eigenvalue problem. Finally it is shown that equal power waveforms are the best transmit signals for the SLS estimator
- Keywords:
- Convex Optimization ; Least Squares Estimation ; Multiple Input Multiple Output (MIMO)System ; Waveforms
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