Theoretical analysis of reconfigurable adaptive antenna array in GNSS applications

Abstract

Traditional adaptive array processing techniques are based on a fixed array configuration. We propose a novel reconfigurable adaptive antenna array strategy in the context of Global Navigation Satellite Systems to add the array configuration as an extra degree of freedom. Specifically we formulate the problem as selecting K from N antennas that are then connected to the following K front-ends and array processing network via switches. The determination of optimal K-antenna subarray configuration can be expressed as a minimization of Spatial Correlation Coefficient (SCC). It denotes the spatial separation between the desired signal and interference. A lower bound of the SCC gives the best achievable performance of all K-antenna subarrays. Two relaxation methods are introduced to obtain the lower bound. The simulation results show that the lower bound formula is reliable in any scenario and the optimum SCC value of an array with more antennas is even larger than the small array under some scenarios. Thus the subarray can reduce both hardware and computational cost dramatically with preserved performance supposing it is optimally configured.