Integrated Range-Doppler Map and Extended Target Classification with Adaptive Waveform for Cognitive Radar
Abstract
We set out to design an extended target classification scheme while determining the target s range-and-Doppler location with the use of adaptive waveform for a closed-loop cognitive radar platform. To that end, this work is divided into three objectives: 1) in support of determining range-Doppler locations, we investigate the ambiguity function of the matched waveform called eigenwaveform, 2) in support of target classification, we look at an adaptive waveform technique called probability-weighted eigenwaveform (PWE) and introduce two new waveforms, and 3) we design an integrated range-Doppler map and extended target classification scheme. In this work, we show that the fundamental properties of ambiguity function for extended targets are different when compared to classical waveforms for point targets. We improve on the adaptive waveform called maximum a posteriori PWE and introduce two new waveforms called match-filtered PWE and two-stage PWE. We propose an integrated range-Doppler map and identification scheme for multiple moving extended targets. Performance comparisons in terms of joint probability of identification and determining targets range-Doppler locations with traditional wideband waveform and the three PWE-based waveforms are shown. It is shown that the three PWE-based waveforms perform better than the classical wideband waveform.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 2014
- Accession Number
- ADA620834
Entities
People
- Jo-yen Nieh
Organizations
- Naval Postgraduate School