Crámer-Rao Bound Analysis for Mixed-ADC Direction of Arrival Estimation in Two-Dimensional Arrays

Digital modulation schemes, such as phase-modulated continuous wave (PMCW) and orthogonal frequency-division multiplexing (OFDM), require high-sampling analog to-digital converters (ADCs), which are power-consuming and costly. As the trend indicates an increase in the number of antennas employed, the issue becomes more critical. Mixed-analog-to-digital converter (ADC) arrays, combining high- and low-resolution ADCs, have recently been investigated to address this issue. In high-resolution radar systems, accurately estimating target positions requires capturing range, Doppler, azimuth, and elevation information. To achieve reliable azimuth and elevation estimation, two-dimensional antenna layouts are essential. Previous studies have focused solely on one-dimensional mixed-ADC assignments, such as uniform linear arrays (ULAs) and sparse linear arrays (SLAs). This paper addresses this problem by providing an analytical derivation of the multivariate Crámer-Rao bound (CRB) for estimating azimuth and elevation jointly in mixed-ADC arrays. Simulation results indicate that optimizing mixed-ADC assignment, i.e., identifying the optimal locations of high- and low-resolution ADCs, enhances the direction of arrival (DoA) estimation accuracy.