Enhanced direction-of-arrival estimation using optimized coprime sensor arrays

Direction-of-arrival (DOA) estimation plays a vital role in modern radar, sonar, wireless communication, and intelligent sensing systems. Conventional uniform linear arrays (ULAs) offer good angular resolution but demand a large number of sensors, increasing hardware cost, power consumption, and processing complexity. Coprime arrays have emerged as a promising sparse sensing architecture that achieves a virtual array with significantly enlarged aperture using only a few physical sensors. This paper presents an enhanced DOA estimation method tailored for coprime array geometry, which effectively exploits the non-uniform sensor placement to increase the degrees of freedom and provide high-resolution estimation even in low signal-to-noise ratio environments. The proposed approach improves robustness against coherent and closely spaced sources by integrating spatial smoothing with an optimized covariance reconstruction strategy. Simulation results demonstrate superior estimation accuracy, reduced RMSE, and better source distinguishability compared to standard ULA-based and existing coprime-array-based techniques.