| Abstrakt: |
Active adaptation to various types of interference from the ground surface is critical for accurately tracking the angles of objects flying at low altitudes. Among the angle-estimation algorithms used in multipath environments, the refined maximum likelihood (ML) technique has been actively investigated. However, it suffers from performance degradation when multiple targets or interference signals exist. In addition, computational complexity increases exponentially as the number of parameters estimated using the refined ML technique increases when multiple targets exist. In this study, we derive an ML estimation formula when two targets are present and propose a refined ML technique for estimating the angles of the two targets by combining the geometric relationship between direct and specular paths with the results of complex envelope estimates using the minimum mean-square-error method. Furthermore, we propose a low-complexity iterative refined ML technique to avoid a two-dimensional grid search. The performance of the proposed algorithm is verified by evaluating its root mean square error and comparing it with those of the conventional refined ML and beam domain ML (BDML). [ABSTRACT FROM AUTHOR] |
