本研究探討了低角度估計技術，並聚焦於三個主要領域：陣列天線技術、數據融合技術和信號處理技術。我們的研究動機是提升低角度目標估計的準確性，並提出改進的擴展卡爾曼濾波(EKF)方法，以補償反射分量對估計結果的影響。我們首先介紹了系統模型，然後詳細描述了EKF及其改進方法，包括多頻EKF技術及其在補償反射分量影響方面的應用。為進一步提高估計性能，我們引入了波束成形技術。模擬結果表明，改進的EKF方法和多頻EKF方法在低角度目標估計中具有顯著優勢，特別是在存在反射分量的情況下。結論部分總結了我們的方法及其效果，並對未來的研究方向提出建議。此研究為低角度估計技術提供了一個有效的解決方案，對相關領域的進一步研究和實際應用具有重要意義。;This study explores low-angle estimation techniques, focusing on three main areas: array antenna technology, data fusion technology, and signal processing technology. Our research motivation is to enhance the accuracy of low-angle target estimation and propose an improved Extended Kalman Filter (EKF) method to compensate for the impact of reflected components on the estimation results.We first introduce the system model, followed by a detailed description of the EKF and its improved methods, including the multi-frequency EKF technique and its application in compensating for the influence of reflected components. To further improve estimation performance,we incorporate beamforming technology.Simulation results indicate that the improved EKF methods and multi-frequency EKF methods have significant advantages in low-angle target estimation, especially in the presence of reflected components. The conclusion section summarizes our methods and their effectiveness, and proposes suggestions for future research directions.This research provides an effective solution for low-angle estimation techniques, which holds significant importance for further research and practicalapplications in related fields.
