Optimization of the Generalized Sinusoidal Frequency Modulated pulse trains for Continuous Active Sonar

2018 
Continuous Active Sonar (CAS) can revisit targets frequently for transmitting long duration waveforms. So developing orthogonal waveforms with good a periodic correlation properties is crucial for enhancing CAS target revisit rate and reducing interferences. This paper aims at designing orthogonal pulse trains which are composed of Generalized Sinusoidal Frequency Modulated (GSFM) waveforms. In order to mitigate interferences, the pulse trains should have lower Auto-correlation Side lobe Peak Level (ASPL) and lower Cross-correlation Peak Level (CPL). Thus, an optimization model is presented for calculating parameters of the pulse trains, and which is solved by Genetic Algorithm (GA) in this paper. The simulation results show that the optimization approach is effective for obtaining GSFM pulse trains with good correlation properties.
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