Research About Detection Method For Foreign Objects Debris On Airport Runways

FOD(Foreign Objects Debris) usually refers to any small objects which does not belong to but located in airport runways. It is necessary to study FOD detection system since these small objects will cause serious security risks and huge economic losses. Currently, some detection equipments have developed in foreign countries; however, there are several domestic products have been published. Therefore, it has an important significance and practical value to study of FOD detection.Since of detection research background, the layout of radar chain that based on specific radar system has been proposed, and detection range of this system has been obtain with reasonable parameters. Secondly, according to the model of echo signal and clutter signal, there are two typical detection methods which used to reduce SCR(Signal-to-Clutter Ratio) of weak targets have been discussed. Finally, CFAR(Constant False Alarm Ratio) detector in multiple target or non-Gaussian background has been analyzed respectively. The main job and innovation are shown as followings:(1) Combined with the airport environment, a bilateral linear deployment of radar chain is proposed; according to parameters such as pitch angle, the height of radar and bandwidth, detailed analysis of detection range and the accuracy of detection are given.(2) An echo signal model is reasonably established based on the system of FOD monitoring radar which is LFMCW(Linear Frequency Modulation Continuous Wave). In order to obtain target information, a weak local oscillator signal which coupled from transmission signal has been mixed with the received signal. A technique of adaptive clutter cancellation which based on Winner-Filtering has been recommended to improve detection probability. In fact, clutter samples are regard as reference signal to estimate the clutter measurements which need to make difference from the actual echo signal.(3) Traditional CFAR methods have ineffective detection performance in nonstationary random clutter. Therefore, two automatic detection methods based on clutter map CFAR has been proposed in this paper. A trimmed-mean clutter map CFAR is used to solve the interference from other strong targets in multiple target environment. In addition, according to the sample-mean and sample-variance, a bi-parameters clutter map CFAR algorithm is proposed to estimated clutter power. Both of theoretical analysis and simulation results indicate that these detectors have better detection performance.