Open AccessWeight Adjusting Algorithm Based on Sensor-space-time Quantum for Air-Information Fusion Precision Evaluation
Author(s) -
Wu Xiao-chao,
Ying Cheng,
Longfei Cui,
Tang Yun-ge
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1213/3/032015
Subject(s) - radar , weighting , computer science , algorithm , benchmark (surveying) , adaptability , sensor fusion , accuracy and precision , fuzzy logic , data mining , real time computing , mathematics , artificial intelligence , statistics , medicine , telecommunications , ecology , geodesy , biology , radiology , geography
The precision index in the performance test of air-information fusion system is one of the important indexes, which benchmark to be determined in complex environment is difficult. This paper proposes a space-time weight adjusting algorithm for the air-information fusion system to solve this problem, as follows: The first is to build the weight priority by the magnitude of radar detection precision; the second is to find the sets of the radars’ time domain that play a dominant role during fusing; the third is to calculate the time cumulate value of radar precision; the fourth is to use the time cumulate value of radar precision and fusion track to allocate all the radar precision weights, and calculate the reference precision by weighting the radar detection data precision; the last is to evaluate the precision index according to fuzzy evaluation method. This algorithm applies to the precision evaluation of the air-information fusion system under the static simulation or dynamic flight conditions with good adaptability and credibility. The simulation shows its value.