Modified OMP method for multi-target parameter estimation in frequency-agile distributed MIMO radar

An Efficient Multi-target Localization Method for Distributed MIMO Radar

This paper studies a multi-target localization method for distributed Multiple-input Multiple-output (MIMO) radar. We assume that the sets of time delays have already been estimated by a pre-processing algorithm. Based on the assumption, we propose a search pairing method based on ellipse model to locate the multi-target. Simulation results demonstrate that the proposed method effectively accom...

Resource Allocation in Distributed MIMO Radar for Target Tracking

Signal Model and Parameter Estimation for Colocated Mimo Radar

In this paper, we consider the signal model and parameter estimation for multiple-input multiple-output (MIMO) radar with colocated antennas on stationary platforms. Considering internal clutter motion, a closed form of the covariance matrix of the clutter signal is derived. Based on the proposed closed form and low rank property of the clutter covariance matrix and by using the singular value ...

Distributed MIMO Radar for Imaging and High Resolution Target Localization

The Air Force Office of Scientific Research supported the research on MIMO radar carried out at the New Jersey Institute of Technology during the period from April 2009 to November 2011 under the agreement number FA9550-09-1-0303. The purpose of this report is to summarize the proceedings and findings of the studies supported by this agreement. The report addresses two broad topics: (i) perform...

Parameter Dynamic Estimation in Near-Field Bistatic MIMO Radar System

—This paper proposes a novel algorithm of parameter dynamic estimation in near-field Bistatic Multiple-Input Multiple-Output (MIMO) Radar. When a target lies in the nearfield region, the near-field wavefront is spherical, and the plane waves assumption is no valid. The existing methods and signal model based on the far-field assumption are not applicable to this situation. In this paper, we pr...