Fusion-Based Direction-of-Arrival (DoA) Estimation with Spatial Diversity in Multi-Cluster Systems

The Direction-of-Arrival (DoA) estimation method is widely investigated under distinct channel impairments such as multipath fading, oscillator phase noise, and the correlation effect with different receiving array structures. In recent years, combination studies such as correlated receive diversity under Rayleigh or Rician fading channels are also considered. The performance investigation of DoA estimation methods for multi-cluster/multi-antenna systems adapts diversity techniques and exploits channel multipath propagation characteristics. A study on DoA estimation performance with a fusion of channel-phase random variables from multiple clusters is not yet explored in the existing research. Therefore, this work investigates the above-case scenario with spatial diversity in multi-cluster systems equipped with multi-antennas. The performance of the proposed scheme is evaluated through extensive Monte Carlo Simulations in MATLAB. The simulation results showed that the fusion-based DoA method reduces estimation errors and performs better through appropriate weight selection mechanisms in receive diversity techniques.

Automated summary

This paper investigates the direction-of-arrival (DoA) estimation method in multi-cluster systems with multiple antennas and spatial diversity. A new DoA estimation method is proposed by fusing channel-phase random variables from multiple clusters. Extensive Monte Carlo simulations demonstrate that the proposed method reduces estimation errors and improves performance through appropriate weight selection mechanisms.