Dimension-Reduced Rx Beamforming Optimized for Simultaneous Detection and Estimation

Abstract

Phased array radar systems are indispensable in many applications requiring robust sensing of the environment. To achieve sensitive target detection and accurate direction-ofarrival (DOA) estimation, a high number of receiving antenna elements is needed. The high dimension of the element level data inevitably leads to a large computational burden for the digital signal processing. This problem can be overcome by transforming the element level data into a lower dimensional beamspace. In this paper, we present a novel parameter-controlled design method to construct this transformation. If the dimension reduction is not too drastic, it jointly achieves optimal detection and DOA estimation performance. Otherwise, it meets pre-defined performance criteria by exploiting an acceptable trade-off between detection and DOA estimation performance. We propose a general design tool, which is not limited to a specific array configuration. The design tool comprises a pre-calculated set of plots, providing the radar designer an overview of possible performance for a given scenario. We describe a straightforward method to construct the corresponding transformation. Numerical studies highlight the superiority of the proposed design method.

Advanced Phase Estimation and Design for Next-Generation Radar Systems: A Digital Approach

“…There must be many receiving antenna elements to detect sensitive targets and accurately estimate the direction of arrival (DOA). Digital signal processing is necessarily burdened with a heavy computing load due to the high dimension of the element-level data [14]. When the pulse repetition interval (PRI) is changed on a regular basis, staggered synthetic aperture radar (SAR) can continuously image an extremely wide area while effectively staggered range blind areas.…”

“…As a result of the changing PRI, azimuth samples are not spread out evenly in a typical staggered SAR. This means that complex resampling processing is needed, including multichannel reconstruction processing and the best linear unbiased (BLU) interpolation [14]. A possible method for the low-cost collection of multiple Doppler weather measurements is multi-static radar.…”