Cy. Tsai et al., TARGET DISCRIMINATION USING NEURAL NETWORKS WITH TIME-DOMAIN OR SPECTRUM MAGNITUDE RESPONSE, Journal of electromagnetic waves and applications, 10(3), 1996, pp. 341-382
Several different memory-based neural networks are used to discriminat
e radar targets based on their early-time, aspect-dependent response.
The beginning of the response is difficult to locate in practice, so w
e use only the magnitude of the time response's DFT Spectrum as input
to the neural network, thus eliminating time-shift, uncertainty. Espec
ially promising is the Recurrent Correlation Accumulation Adaptive Mem
ory-Generalized Inverse (RCAAM-GI) cascade neural network. From the si
mulation results, the network demonstrates a decision strategy which i
s flexible, parallel adaptive, computation space efficient, and highly
noise tolerant. Performances of the networks presented in this paper
are compared with those of existing networks.