What is it about?
The paper investigates how the performance of a matched filter varies when the noise changes from stationary to non-stationary. Matched filter is known to maximise the SNR of the received signal when the noise in the model is assumed to be white and non-stationary. In underwater acoustic sensing applications, the non-constant gain to compensate for transmission loss often restores the received signal but changes the noise in the received signal, so that the noise is no longer stationary. A matched filter would no longer be an optimal receiver filter for such a scenario.However, we prove that a filter designed to maximise the SNR for a signal signal received in such noise is conditionally optimal for very long signals and at short ranges only; the matched filter is still the best choice for all signal lengths and all ranges.
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Why is it important?
The research strengthens the fact the matched filter, a generic receiver filter, known to maximise the SNR of the received signal, is the optimal choice, regardless of the type of the noise. This is, at least true for underwater sensing applications, where a Time Variable Gain is used to compensate for non-constant transmission loss.
Read the Original
This page is a summary of: The Sensitivity of the Matched Filter Signal to Noise Ratio and Effects of Time Variable Gain for Sonar Systems, IET Radar Sonar & Navigation, December 2019, the Institution of Engineering and Technology (the IET), DOI: 10.1049/iet-rsn.2019.0334.
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Doppler Tolerant Code Optimisation Scheme for Multi-code Sonar Systems
Underwater acoustic sensing (i.e., sonar) requires probing signals to have a narrow auto-correlation peak with minimal autocorrelation sidelobe levels and minimal crosscorrelations. Another requirement is that the signals should be robust to Doppler effects. Codes achieving the ideal in all these characteristics simultaneously are not possible and compromises must be made in designing probing signals. In this research, we use a novel gradient-descent algorithm for optimising sets of multiple codes for desirable correlation properties while being robust to Doppler scaling. We constrain our optimised code-sets to follow a specific power profile while maintaining a Peak-to-Average Power Ratio (PAPR) close to 1. The codes are optimised for multiple Doppler scaling factors for different source/target speeds. We show that by slightly increasing the mainlobe width from a single sample, lower SLLs can be achieved. This makes our codes flexible for a wide range of applications. The optimised codes from the algorithm have superior characteristics when compared to codes previously published.
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