Naïve Bayes For Radar Micro-Doppler Recognition

Mere som dette

the founder

af Daniela Medina

Abortion

af Wiesner Wiesner

hybrid Vs combustion engines

af james wakefield

SPS 170

af mohd fadhil baharudin

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