a Graeme Smith 17 éve
380
Naïve Bayes For Radar Micro-Doppler Recognition
The document encompasses a comprehensive exploration of using the Naïve Bayes classifier for recognizing radar micro-Doppler signatures. It begins with an introduction that reviews relevant papers and discusses the motivation and background for the work.
Megnyitás
Naïve Bayes For RadarMicro-Doppler Recognition 5. Test Strategy Analysis Of Classifier at ±5% Assessment Of Variance 7. Conclusions The Pre Processing Steps Performance Of Naïve Bayesian Use Of Bhattacharyya Bound 6. Results Datasets Size
Correlation
Frames Duration
Parameters R
Pfa
Pdec
Pcc
Variance Performance Range Max 95%
Step 5%
Min 45%
4. Performance Prediction Assumptions Sufficient Data To Estimate μ and Σ Equal Prior Probabilities Probability Distributions Multivariate Guassians
Bhattacharyya Bound Limits Sub-Optimal
Better
Difficult
Chernoff
Binary
Cases Vehicles vs Tracked
Tracked vs Personnel
Wheeled vs Tracked
Wheeled vs Personnel
Probability Of Error 2. Data Test Reference Pre-Processing Principal Component Analysis Normalizing Clutter FFT Power
Decibel
Absolute
Micro-Doppler Unknown Classes Tracked
Personnel
Wheeled
Thales 3. Naïve Bayesian Classifier Assumption Validity Not Perfect
Improved By PCA
Independence Definition 1. Introduction Review Of Relvant Papers Motivation For Work Background
