偵測距離、速度和加速度的高效能演算法

Abstract

汽車雷達主要用在提升行車的舒適與安全性。可適性恆速裝置、停車輔助系統、碰撞避免以及碰撞預測，都取決於座標、速度和加速度的準確估算。我們提出一個新方法，從FMCW的反射訊號估計座標、速度和加速度。Minimum-delay one-stage Kalman filters被用來準確估計加速度，最後我們採用汽車轉彎的例子做驗證。 我們另推導出一套，combination of two-stage and one stage Kalman filters，用來估計加速度，並用於船艦，估算近距離的飛彈位置。

Automotive radar sensors have been used to ensure comfort and safety. Adaptive cruise control (ACC), parking aid, collision avoidance, and pre-crash detection are applications pending on the accurate estimation of target location, velocity and acceleration. A new process by taking the measured FMCW echoes to estimate the range, velocity and acceleration of the moving target. Minimum-delay one-stage Kalman filters are proposed to calculate the acceleration accurately. Demonstration is given with a vehicle making a turn across the adjacent lane in front of the host vehicle. We also propose a new process by taking the measured FMCW echoes to estimate the range and velocity of a moving target. Combination of two-stage and one-stage Kalman filters are proposed to estimate the acceleration accurately. Demonstration is given with a missile making a turn to attack a ship.