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Principles of Modern Radar - Volume 2 1891121537

Principles of Modern Radar - Volume 2 1891121537

Principles of Modern Radar - Volume 2 1891121537

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178 CHAPTER 5 <strong>Radar</strong> Applications <strong>of</strong> Sparse Reconstruction110.50.500 2 400 2 4110.50.500 2 400 2 4110.50.500 2 400 2 4FIGURE 5-7 An example application <strong>of</strong> OMP to a simple radar problem. The signal <strong>of</strong> interestis a set <strong>of</strong> three-point scatterers. The collected data represent the returns from a single pulsewith 500 MHz <strong>of</strong> bandwidth. Each row depicts a single iteration <strong>of</strong> the OMP algorithm. Thepanes on the left depict the backprojected residual A H ( y − A ˆx) at each iteration. The rightpanes depict the signal estimate ˆx with a curve and the true signal x true with crosses.obtain a RIP-based guarantee <strong>of</strong> the same form as others that we have seen. In particular,if R 4s (A) ≤ 0.1 [39], then∥ x true − ˆx ∥ 2≤ 20 [∥∥ x true − x true∥2+ s −1/2 ∥∥ x true − x true∥1+ σ ] (5.37)sIn addition, CoSaMP will converge, assuming exact arithmetic, in at most 6(s + 1) iterations.This guaranteed convergence and numerical simplicity come at a price. In particularthe requirement on the RIC is more stringent and the error bound is looser. A comparison<strong>of</strong> IHT, CoSaMP, and BP for noise-free signals can be found in [94]. A detailed numericalinvestigation along with parameter tuning strategies comparing CoSaMP and SP to iterativethresholding algorithms can be found in [95]. As we shall see one advantage <strong>of</strong> thesegreedy approaches is that they can be easily extended to cases where signal knowledgebeyond simple sparsity is available.s5.3.5 Bayesian ApproachesWe have already mentioned the interpretation <strong>of</strong> QP λ as the MAP estimate under a Laplacianprior. Several efforts have been made to apply other priors to the vector x true to achievesparse solutions. Many <strong>of</strong> these approaches seek minimum mean square error (MMSE)estimates <strong>of</strong> the signal.5.3.5.1 Averaging SolutionsThe first example along these lines is a randomized version <strong>of</strong> OMP described in [96].Instead <strong>of</strong> always selecting the atom having the largest correlation with the remainingresidual, this algorithm selects the next atom at random with a distribution whose

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