Distributed Target Detection with Partial Observation via Matrix Completion
نویسندگان
چکیده
This paper considers the detection of a distributed target, which is important in high resolution radars (HRRs). We focus on the practical scenario where only partial observation is available. The key contribution of this work is the proposition of a generalized likelihood ratio test (GLRT) detector using matrix completion (MC). Firstly, a decision rule is obtained for the hypothesis test model with missing data. Then the estimation of the unknown parameters involved in the detector is derived via the maximum-likelihood estimator (MLE). To overcome the problem that the full covariance matrix of the disturbance can not be estimated analytically, we adopt the MC technique, in which the estimate is obtained by solving an optimization problem concerning both the MLE expression and the low rank interference. An alternating iterative algorithm is followed to achieve the final estimate. Numerical results are presented to validate the effectiveness of the proposed method when the missing data problem occurs.
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