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Showing 1 to 4 of 4 for “"MIMO radars"”.

  1. Contemporary Approaches to Radar Detection: Robust Statistics, Reinforcement Learning, and Reconfigurable Intelligent Surfaces

    … This work focuses only on monostatic co-located MIMO radar and radar networks. First, we look at the role of robust detection statistics and RL in radar detection. Because RL is a type of online learning, RL based radar detection is well suited for dynamic environments; however, typically, …

    vt Repository record for Contemporary Approaches to Radar Detection: Robust Statistics, Reinforcement Learning, and Reconfigurable Intelligent Surfaces (opens in a new tab)

  2. Generalized DFT: extensions in communications

    … in order to deliver better performance. For MIMO Radar systems, the ideal case to detect a moving target is when all waveforms are orthogonal, which can provide an accurate estimation. But this is not practical in distributed MIMO radars, where sensors are at varying distances from a target. …

    njit Repository record for Generalized DFT: extensions in communications (opens in a new tab)

  3. Global optimization methods for localization in compressive sensing

    … localization in multiple-input multiple-output (MIMO) radars. Compressive sensing is a paradigm at the intersection between signal processing and optimization. It advocates the sensing of "sparse" signals (i.e., represented using just a few terms from a basis expansion) by using a sampling rate …

    njit Repository record for Global optimization methods for localization in compressive sensing (opens in a new tab)

  4. Target localization in MIMO radar systems

    MIMO (Multiple-Input Multiple-Output) radar systems employ multiple antennas to transmit multiple waveforms and engage in joint processing of the received echoes from the target. MIMO radar has been receiving increasing attention in recent years from researchers, practitioners, and funding …

    njit Repository record for Target localization in MIMO radar systems (opens in a new tab)