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—For reconstruction of low-rank matrices from under-sampled measurements, we develop an iterative algorithm based on least-squares estimation. While the algorithm can be used for any low-rank matrix, it is also capable of exploiting a-priori knowledge of matrix structure. In particular, we consider linearly structured matrices, such as Hankel and Toeplitz,(More)
—The implementation challenges of cooperative local-ization by dual foot-mounted inertial sensors and inter-agent ranging are discussed and work on the subject is reviewed. System architecture and sensor fusion are identified as key challenges. A partially decentralized system architecture based on step-wise inertial navigation and step-wise dead reckoning(More)
—For compressive sensing of dynamic sparse signals, we develop an iterative pursuit algorithm. A dynamic sparse signal process is characterized by varying sparsity patterns over time/space. For such signals , the developed algorithm is able to incorporate sequential predictions, thereby providing better compressive sensing recovery performance, but not at(More)
In this paper, we propose a robust transmit beampattern design for multiple-input multiple-output (MIMO) radar systems. The objective considered here is minimization of the beampattern sidelobes, subject to constraints on the transmit power where the waveform co-variance matrix is the optimization variable. Motivated by the fact that the steering vectors(More)
—Pedestrian Dead-Reckoning (PDR) and Radio Frequency (RF) ranging/positioning are complementary techniques for position estimation but they usually locate different points in the body (RF in the head/hand and PDR in the foot). We propose to fuse the information from both navigation points using a constraint filter with an upper bound in the distance between(More)
—For line spectrum estimation, we derive the maximum a posteriori probability estimator where prior knowledge of frequencies is modeled probabilistically. Since the spectrum is periodic, an appropriate distribution is the circular von Mises distribution that can parameterize the entire range of prior certainty of the frequencies. An efficient alternating(More)