Airport runway foreign matter detection method and device based on characteristics of characteristic spectrum

A foreign object detection and airport runway technology, applied in the field of radar, can solve the problems of waste of time and resources, complex scattering characteristics of airport runways, etc., and achieve the effect of small error

Active Publication Date: 2017-10-10
SOUTHWEST CHINA RES INST OF ELECTRONICS EQUIP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, due to the complex scattering characteristics of the airport runway, the probability of false alarms in the FOD detection process of the

Method used

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  • Airport runway foreign matter detection method and device based on characteristics of characteristic spectrum
  • Airport runway foreign matter detection method and device based on characteristics of characteristic spectrum
  • Airport runway foreign matter detection method and device based on characteristics of characteristic spectrum

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specific Embodiment 1

[0090] According to the parameters of the classifier, the optimal classification surface is obtained, and the feature vector of the test sample (FOD echo) is judged according to the optimal classification surface. Among them, all false alarm signals fall within the optimal classification surface. If there is no signal, it means that there is no FOD on the runway before the plane takes off, otherwise, it means that there is FOD on the runway before the plane takes off. Specific embodiment 1, two kinds of features feature1 and feature2 are extracted from the test sample (FOD echo), and the trained classifier is used to classify the two kinds of features used for testing.

[0091] For the test sample, use the trained minimum and maximum probability machine to classify it according to the following steps:

[0092] 6a) performing feature extraction on the test sample to obtain a feature vector f={feature1, feature2} formed of the two features for testing;

[0093] 6b) Input the fe...

specific Embodiment 2

[0098] Specific embodiment two: (can replace the implementation process of step 61); extract two kinds of features from the test sample set, and use the trained classifier to classify the two kinds of features used for testing.

[0099] For the test sample, utilize the trained minimum maximum probability machine to classify it according to the following steps: 6a) carry out feature extraction for the test sample, obtain the feature vector f={feature1, feature2};

[0100] 6b) Use the two features corresponding to the background clutter data feature vector and the background clutter data label to train the minimum and maximum probability machine classifier, and obtain the minimum and maximum probability machine classifier parameter a opt and b opt ; where a opt is the optimal solution of the minimum maximum probability machine; b opt = 1;

[0101] 6c) According to parameter a opt and b opt Obtain the optimal classification surface, and judge the FOD echo feature vector acc...

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Abstract

The invention relates to the technical field of radars, and aims to solve the problems existing in the prior art. The invention provides an airport runway foreign matter detection method and a device based on the characteristics of a characteristic spectrum. According to the invention, the FOD detection at a low false alarm probability is realized. Runway benchmark background data are adopted as clutter map reference data, and the clutter map constant false-alarm rate (CFAR) treatment is carried out on runway radar data. After the clutter map constant false-alarm rate (CFAR) treatment of the runway radar data, obtained data are classified and divided into a background clutter signal and an FOD echo including a false alarm signal. The characteristic values of the background clutter signal and the FOD echo signal are respectively calculated, and then corresponding characteristics are extracted to form corresponding characteristic vectors according to corresponding characteristic values. A characteristic vector corresponding to the background clutter signal and the label of the background clutter signal are trained by a classifier, and then the parameters of the classifier are obtained. Whether an FOD exists in the FOD echo or not can be judged according to a characteristic vector corresponding to the characteristic value of the FOD echo signal and the parameters of the classifier. Therefore, the FOD detection of a runway is realized.

Description

technical field [0001] The invention relates to the technical field of radar, in particular to a method and device for detecting foreign objects on an airport runway based on characteristic spectrum features. Background technique [0002] Foreign Object Debris (FOD) on the airport runway refers to objects that should not exist on the airport runway and cause damage to the aircraft, such as metal parts, broken stones, waterproof plastic sheets, etc. left on the runway. FOD poses a serious threat to aircraft takeoff and landing and must be removed before the aircraft takes off. The traditional manual inspection method consumes a lot of time, which affects the amount of aircraft commuting on the airport runway. At the same time, it is not easy to rely on manual detection of small foreign objects in bad weather such as rain and fog. Therefore, it is necessary to develop an automatic detection of foreign objects on the airport runway. The system can monitor the runway environmen...

Claims

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Application Information

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IPC IPC(8): G01S7/292G01S7/35G01S7/41G01S13/04G01S13/91
CPCG01S7/2927G01S7/354G01S7/41G01S13/04G01S13/91G01S2013/916
Inventor 王宝帅王小斌刘江洪郑小亮贺岷珏肖庆
Owner SOUTHWEST CHINA RES INST OF ELECTRONICS EQUIP
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