Signal processing of Frequency Diverse Array Radars for Satellite range Estimation

Abstract

The potential advantages of frequency diverse array (FDA) Radars, particularly in target direction and range estimation are numerous. Despite their ability, the angle-range-dependent beampattern of FDA Radars introduces challenges of angle-range coupling, necessitating the decoupling of angle and range estimates for accuracy. Conventionally Subspace based methods have been used for range and angle estimation in FDA radars, these methods provide low resolution parameter estimation, and are less accurate and require several measurement pulses to achieve required accuracy. A small error in angle estimation can be neglected at lower ranges, but for targets at larger distances even a small error in angle correspond to a larger distance. To address this, an integration of FDA technology with multi-input multi-output (MIMO) systems is used, forming FDA-MIMO radar systems that exploit MIMO’s high degree-of-freedom (DOF) for improved estimation. In this thesis various sparse reconstruction methods have been used for enhancing the angular accuracy of FDA-MIMO radar.