Abstract
Non-uniform linear arrays (NULAs) often achieve better resolution than standard uniform linear arrays (ULAs) with equal numbers of sensors. However, conventional beamforming (CBF) of an NULA received signal leads to the same detection statistic PDF as a ULA with the equal number of sensors, undercutting NULA's improved resolution. Nested and coprime arrays partition an NULA into two subarrays and multiply the subarrays' CBF outputs. This research compares this product processor's detection performance against a CBF detector with an equal number of sensors for a narrowband Gaussian signal in spatially white additive Gaussian noise. The product processor's detection PDF is a scaled product of the detection statistic with modified Bessel functions. Receiver operation characteristics (ROC) curves illustrate that the product processor's performance is inferior to the CBF detector with an equal number of sensors. The detection performance of a product processor matches the CBF detector only for high SNRs and large numbers of sensors. However, in the presence of interferers, the product processor for coprime arrays can outperform both the CBF detector and product processing nested arrays with an equal number of sensors. [Work supported by ONR.]