Time domain threshold crossing for signals in noise

This work investigates the discrimination of times between threshold crossings for deterministic periodic signals with added band-limited noise. The methods include very low signal to noise ratio (one or less).Investigation has concentrated on the theory of double threshold crossings, with especial care taken in the effects of correlations in the noise, and their effects on the probability of detection of double crossings. A computer program has been written to evaluate these probabilities for a wide range of signal to noise ratiOS, a wide range of signal to bandwidth ratios, and a range of times between crossings of up to two signal periods. Correlations due to the extreme cases of a Brickwall filter and a second order Butterworth filter have been included; other filters can easily be included in the program.The method is simulated and demonstrated by implementing on a digital signal processor (DSP) using a TMS32020. Results from the DSP technique are in agreement with the theoretical evaluations.Probability results could be used to determine optimum time thresholds and windows for signal detection and frequency discrimination, to determine the signal length for adequate discrimination, and to evaluate channel capacities.The ability to treat high noise, including exact effects of time correlations, promises new applications in electronic signal detection, communications, and pulse discrimination neural networks

The application of auditory signal processing principles to the detection, tracking and association of tonal components in sonar.

A steady signal exerts two complementary effects on a noisy acoustic environment: one is to add energy, the other is to create order. The ear has evolved mechanisms to detect both effects and encodes the fine temporal detail of a stimulus in sequences of auditory nerve discharges. Taking inspiration from these ideas, this thesis investigates the use of regular timing for sonar signal detection. Algorithms that operate on the temporal structure of a received signal are developed for the detection of merchant vessels. These ideas are explored by reappraising three areas traditionally associated with power-based detection. First of all, a time-frequency display based on timing instead of power is developed. Rather than inquiring of the display, "How much energy has been measured at this frequency? ", one would ask, "How structured is the signal at this frequency? Is this consistent with a target? " The auditory-motivated zero crossings with peak amplitudes (ZCPA) algorithm forms the starting-point for this study. Next, matters related to quantitative system performance analysis are addressed, such as how often a system will fail to detect a signal in particular conditions, or how much energy is required to guarantee a certain probability of detection. A suite of optimal temporal receivers is designed and is subsequently evaluated using the same kinds of synthetic signal used to assess power-based systems: Gaussian processes and sinusoids. The final area of work considers how discrete components on a sonar signal display, such as tonals and transients, can be identified and organised according to auditory scene analysis principles. Two algorithms are presented and evaluated using synthetic signals: one is designed to track a tonal through transient events, and the other attempts to identify groups of comodulated tonals against a noise background. A demonstration of each algorithm is provided for recorded sonar signals