Automotive radars for potential accident reduction and for autonomous cruse control were available in 1999, and 77 GHz long-range radars and 24 GHz short-range radars are developing [1]. 79-GHz shortrange automotive radars have a bandwidth of 4 GHz, a maximum range of 30 m, and a range resolution of 5 cm. Radar reception signals often contain unwanted echoes, called “radar clutter.” Moving targ...

An adaptive target detector in radar system is used to extract targets from background in noisy environment of unknown statistics. The constant false alarm rate (CFAR) is well known detection algorithm that is being used in almost every modern radar. The cell averaging CFAR is the optimum detector in homogeneous clutter environment when the refence cells have identically independent and exponen...

Generalized Order Statistic Cell Averaging (GOSCA), Generalized Order Statistic Greatest Of (GOSGO), and Generalized Order Statistic Smallest Of (GOSSO) CFAR detectors are proposed. Each of them has its own advantages according to radar environment situations so that most effective radar detector can be chosen at any unpredictive situation. Their performance formulas in terms of false alarm pro...

A hardware architecture that implements a CFAR processor including six variants of the CFAR algorithm based on linear and nonlinear operations for radar applications is presented. Since some implemented CFAR algorithms require sorting the input samples, the two sorting solutions are investigated. The first one is iterative, and it is suitable when incoming data clock is several times less than ...

This paper deals with the distributed constant false alarm rate (CFAR) radar detection of targets embedded in heavy-tailed Pearson distributed clutter. In particular, we extend the results obtained for the cell averaging (CA), order statistics (OS), and censored mean level CMLD CFAR processors operating in positive alpha-stable (P&S) random variables to more general situations, specifically to ...

This paper presents a new approach to Constant False Alarm Rate (CFAR) data fusion using Fuzzy Integration. The paper describes how any CFAR scheme may be implemented as part of a fuzzy data fusion scheme by choosing an appropriate membership function to represent the CFAR threshold. Once the threshold membership function of the Fuzzy Integrator has been set up, the false alarm rate of the sche...

In this paper, we address the cell averaging (CA), greatest of (GO), and smallest of (SO) constant false alarm rate (CFAR) processors for code acquisition in homogeneous and nonhomogeneous environment. The performance characteristics of the CA, GO, and SO processors are obtained and compared when receiving antenna diversity is employed in the pseudonoise code acquisition of direct-sequence code...

An artificial intelligence system improves radar signal processor performance by increasing target probability of detection and reducing probability of false alarm in a severe radar clutter environment. This utilizes advances in artificial intelligence and expert systems technology for the development of data analysis and information (signal) processors used in conjunction with conventional (de...

This paper considers the radar scenes which contain numerous rapidly changing terrains, i.e., there are more than one clutter-edge in the environment. This kind of radar scenes incurs sharply degradation in the performance of the present adaptive constant false alarm rate (CFAR) detectors as the statistical characteristic of reference cells is highly heterogeneous. To solve this problem, we pro...