Titlebook: Radar Signal Processing and Its Applications; Jian Li,Robert Hummel,Edmund G. Zelnio Book 2003 Springer Science+Business Media Dordrecht 2

AXIS

马具

Wavelet Transformation and Signal Discrimination for HRR Radar Target Recognition,ow that by iteratively applying this approach, classifier performance is improved. The number of times the feature reduction and transformation can be performed while producing improved classifier performance is small and the transformed features are shown to quickly cause the performance to approac

pineal-gland

2D HRR Radar Data Modeling and Processing,r and target parameters for the model. This simplification process produces two HRR radar models with different degrees of simplicity. After establishing this set of models, the typical HRR data processes, such as feature extraction and clutter suppression, are reduced to one problem, which is model

Nebulizer

薄膜

Nomadic

Inertia

强化

FILLY

Target-Centered Models and Information-Theoretic Segmentation for Automatic Target Recognition,s to produce a consistent segmentation over all poses. We present performance and computation complexity results as a function of segmentation threshold, confuser-rejection threshold, and operating conditions for publicly available SAR data.

judiciousness

Experimental Evaluation of Adaptive Beamforming Methods and Interference Models for High Frequency mforming algorithms with robustness against “jammer motion” are also described and their effectiveness is experimentally demonstrated using interference data collected by 32 narrowband receivers of the very wide aperture (2.8 km) Jindalee OTH radar uniform linear array located near Alice Springs in central Australia.