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Item A technique for pulse RADAR detection using RRBF neural network(2012) Sahoo A.K.; Panda G.; Majhi B.Pulse compression technique combines the high energy characteristic of a longer pulse width with the high resolution characteristic of a narrower pulse width. The major aspects that are considered for a pulse compression technique are signal to sidelobe ratio (SSR), noise and Doppler shift performances. The traditional algorithms like autocorrelation function (ACF), recursive least square (RLS) algorithm, multilayer perceptron (MLP), radial basis function (RBF) and recurrent neural network (RNN) have been applied for pulse compression and their performances have also been studied. This paper presents a new approach for pulse compression using recurrent radial Basis function (RRBF) neural network. 13 and 35-bit Barker codes are taken as input to RRBF network for pulse compression and the results are compared with MLP, RNN and RBF network based pulse compression schemes. The analysis of simulation results reveals that RRBF yields higher SSR, improved noise performance, better Doppler tolerance and hence more robust for pulse radar detection compared to the other techniques. � 2012 Newswood Limited. All rights reserved.Item Sidelobe suppression using convolutional windows in radar(2012) Sahoo A.K.; Panda G.The matched filter output of pulse compression radar is associated with range sidelobes along with the mainlobe. To reduce these sidelobes, different types of windows are used as weighing function at the receiver. When the target is in motion, the reflected signal is Doppler-shifted version of the original transmitted signal. If this Doppler-shifted signal is passed through the receiver matched filter, it produces very low Peak to Sidelobe Ratio (PSR). In this paper, we have proposed the use of convolutional windows at the receiver along with amplitude tapered or phase distorted transmitted Linearly Frequency Modulated (LFM) signal to get high PSR value in Doppler shift condition. Exhaustive simulation studies are carried out for Time-Bandwidth (TB) product of 50 and 100 and it is found that convolutional windows provide superior PSR performance over conventional windows. � 2012 Inderscience Enterprises Ltd.