Correlation method for flight tracks of airborne radar and infrared sensor

Abstract

The invention discloses a correlation method for flight tracks of an airborne radar and an infrared sensor. According to the method, angle information observed by the airborne radar and the infrared sensor is fully utilized, wherein the angle information comprises an azimuth angle and a pitch angle. The correlation method comprises the steps of: on the basis of ambiguous comprehensive functions, establishing comprehensive discrimination functions by utilizing the observed information of the airborne radar and the infrared sensor; formulating a decision criterion; and finally determining judgment thresholds through counting characteristics and a correlation rate of the comprehensive judgment functions and then carrying out related judgment. The correlation method for the flight tracks of the airborne radar and the infrared sensor has the positive effect that on the basis of researching the sensor measurement origin uncertainty problem, by taking the airborne radar and the infrared sensor as examples, a driving / driven sensor flight track correlation method is disclosed on the basis of an ambiguous comprehensive theory; and the driving / driven sensor flight track correlation method not only can be used for solving the measurement origin uncertainty problem of multi-sensor observed information, but also can be applied to the flight track correlation problems related to multi-sensor multi-target tracking in the military or civil field.

Description

technical field [0001] The invention relates to a method for associating an airborne radar with an infrared sensor track. Background technique [0002] Maneuvering target tracking is a typical uncertainty problem, and its uncertainty mainly manifests as the uncertainty of target motion state and the uncertainty of sensor measurement origin. [0003] In the dual-sensor detection system composed of radar / infrared sensors, the radar has high tracking accuracy and comprehensive collection, including distance information and angle information, but its interference ability is poor; the infrared sensor can only measure angle information, and the angle tracking accuracy is high. It has strong anti-interference ability. Using the respective advantages of the two sensors for combined tracking, on the one hand, the signals received by each sensor can be used for fusion, and on the other hand, different information provided by each sensor can be used to achieve reliable decision-making...

AI Technical Summary

Problems solved by technology

At present, the traditional track correlation algorithm includes weighting method, correction method, nearest neighbor method, etc., but in the dense target environment, the traditional track correlation algorithm has a low correlation accuracy rate, and when the system includes large navigation, sensor These methods are powerless when it comes to calibration and conversion and delay errors, and the above-mentioned traditional track correlation algorithms will face many difficulties when applied to active and passive sensor data association

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