GNSS direct positioning estimation based on distributed antenna arrays in harsh propagation conditions

Global Navigation Satellite Systems (GNSS) receivers often fail to deliver reliable position solutions in harsh propagation environments due to signal blockage and multipath. Direct position estimation (DPE) improves robustness by operating directly on the received signals; however, conventional DPE does not fully exploit the geometric diversity provided by distributed receivers and correlation available in multi-antenna observations. This paper proposes a distributed array-DPE framework that jointly processes signal-domain observations collected by spatially separated multi-antenna receivers through a unified signal reception model. An equivalent navigation-domain maximum-likelihood (ML) cost function is derived for joint processing across all arrays. The Cramér–Rao lower bound (CRLB) is derived as a lower-bound reference to characterize the information gain from antenna array and distributed receivers observations. Monte Carlo simulations under blockage and multipath conditions show that the proposed method substantially reduces the root-mean-square error (RMSE) compared with distributed single-antenna DPE (DSA-DPE).