PAT and Px code sidelobe reduction using wavelet neural network
Pulse compression is a significant aspect for improving the radar detection and range resolution. To improve the range detection, the pulse width is increased to overcome the transmitter maximum peak power limitations. However, pulse compression is accompanied with time sidelobes that can mask the s...
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| Main Authors: | , , , |
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| Format: | Article |
| Published: |
Springer International Publishing
2016
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/8567/ |
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| Summary: | Pulse compression is a significant aspect for improving the radar
detection and range resolution. To improve the range detection, the pulse width is
increased to overcome the transmitter maximum peak power limitations. However,
pulse compression is accompanied with time sidelobes that can mask the small
targets. The Wavelet Neural Network (WNN) is a new technique used for pulse
compression sidelobe reduction. In this paper, Morlet function is applied as an
activation function for WNN and the backpropagation (BP) is implemented for
training the networks. The WNN is applied based on PAT and Px polyphase codes.
The performance of WNN is evaluated in terms of Signal to Noise Ratio (SNR) and
the computational complexity. The simulation results indicate that the WNN has
higher Peak Sidelobe Level (PSL) than the Auto Correlation Function (ACF) with
more than 100 dB and higher PSL than the Neural Network (NN) with more than
100 dB. |
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