Radio Frequency Interference (RFI) is a significant threatto the successful operation of Global Navigation SatelliteSystems (GNSS) receivers. Thus adaptive antenna arrayshave been proposed to mitigate broadband interference andmultipath in GNSS applications. However the high cost, interms of both hardware and computational load, of a largearray makes adaptive array processing a luxury for civilianGNSS receivers. In order to reduce the high cost whilepreserving the performance, we propose in this paper areconfigurable adaptive antenna array strategy, where we“choose K from N antennas” that are then connected to thefollowing front-ends and beamforming network. Then thecorresponding beamforming weight vector is developedbased on the chosen subarray to obtain the maximuminterference suppression adaptively.The Spatial Correlation Coefficient (SCC) is introduced inthis paper to characterize the effect of the arrayconfiguration on the processing performance. Subarrayselection in terms of minimizing the SCC is an NP-hardcombinatorial optimization problem. In this paper weadopt a reweighted l_1 -norm regularization method to selectthe subarray. As we seek a binary solution, we modify thismethod in order to satisfy binary entry requirement of thesparse solution. The experimental results havedemonstrated the effectiveness and efficiency of theproposed method.The focus of this paper is on implementing our proposedsubarray selection strategy in a real GPS experiment.Firstly the arrival directions of both satellite signals and the interference are estimated and then an adaptive antennaarray is utilized to suppress the strong interference andenhance the cross correlation performance. Secondly, theproposed l_1 -norm method is employed to choose anoptimum subarray. The effective carrier to noise densityratio (effective C/N_o ) is adopted as a metric to measurethe performance and the trade-off curve is utilized to showthe compromise between the performance and the cost.Experimental results demonstrate that SCC is a convenientparameter to characterize the impact of array configurationon the adaptive array processing performance. The utilityof adaptive antenna array reconfiguration in order toachieve minimum cost with maximum preservedperformance is also proved.
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