近頻干擾下之強化有序統計量恆虛警率 FMCW檢測

Abstract

近年來，頻率調變連續波雷達(Frequency Modulated Continuous Wave Radar)應用在汽車雷達系統上日見普遍，舉凡Mercedes-Benz, BMW, VOLVO等車廠都相繼將之應用於主動式安全系統上，例如適應性巡航控制(Adaptive Cruise Control, ACC)、智慧型停走系統(Stop & Go)、智慧型防撞系統(Collision Avoidance)等。但當FMCW Radar大量被應用後，隨之而來的是信號相互之間的干擾，在此情況下將無法有效偵測出目標。在本論文中，我們探討近頻干擾(Similar-Frequency Interference)的情況，並提出一個新的FMCW Radar架構來測得近頻干擾的存在。在近頻干擾情況下，典型的有序統計量恆虛警率(Ordered Statistic CFAR, OS-CFAR)檢測能力將會降低，藉由測得近頻干擾情況下得到的資訊，我們提出自適應Adaptive OSGO-CFAR (Ordered Statistic Greater-of CFAR, OSGO-CFAR)方法，並利用配對機制來改善其偵測能力，經由模擬結果顯示可以驗證我們提出的方法，確實可有效偵測近頻干擾下的多目標。

In recent years, the Frequency Modulated Continuous Wave (FMCW) Radar has been widely adopted in automotive radar systems. Automakers such as Mercedes-Benz, BMW and VOLVO are applying it to active safety systems, e.g. Adaptive Cruise Control, Stop & Go and Collision Avoidance. With the prevalence of FMCW radars, the interference between signals emerges. In this case, targets cannot be effectively detected. In this thesis, we study the scenario of similar-frequency interference (SFI) and propose a new architecture to identify the presence of SFI. In the presence of SFI, performance of conventional Ordered Statistic Constant False Alarm Rate (OS-CFAR) detection will be degraded. With the aid of interference identification, we propose a new method, called Adaptive Ordered Statistic Greater-of CFAR (OSGO-CFAR), and utilize a pairing mechanism to improve the detection capability. Simulation results confirm the efficacy of the proposed detection method under SFI.