Reduced-dimensional angle estimation in bistatic MIMO radar system

Abstract

An algorithm for reduced-dimensional angle estimation in bistatic Multiple-Input Multiple-Output (MIMO) radar system is presented. By utilizing the characteristic of Kronecker product, two-dimensional search of Capon/MUSIC can be reduced. The direction-of-arrivals (DOAs) and directionof-departures (DODs) can be obtained by one-dimensional search and eigenvectors corresponding to the smallest eigenvalues, respectively. Furthermore, the angles of targets can be paired automatically. Simulations which demonstrate the analytical derivations are provided.

Kalman filtering method for sparse off‐grid angle estimation for bistatic multiple‐input multiple‐output radar

“…Angle estimation plays a vital role in array signal processing. This has led to the development of varied estimation algorithms like minimum‐norm and the least‐square techniques [7], propagator method [8], reduced‐dimensional (RD) [9, 10] and signal subspace reconstruction method [11, 12].…”

A time‐varying angle extraction method for refined proximity group targets tracking

“…Because the change of the target angle will affect the angle estimation accuracy even in the same beam, so it is more appropriate to use across-angle unit instead of ABU. Super-resolution angle estimation methods are commonly used in angle estimation methods of single-echo, such as multiple signal classification (MUSIC), estimating signal parameter via rotational invariance techniques (ESPRIT) [9][10][11] etc. For a single objective, these algorithms have a common feature, to solve the optimisation problem of a single variable based on one criterion.…”