类别 全部 - performance - variance

作者:Graeme Smith 17 年以前

364

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.

Naïve Bayes For Radar Micro-Doppler Recognition

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