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This paper uses advanced time-frequency signal analysis techniques to generate new models for bio-inspired sonar signals. The inspiration comes from the analysis of bottlenose dolphin clicks. These pulses are very short duration, between 50 and 80 micros, but for certain examples we can delineate a double down-chirp structure using fractional Fourier methods. The majority of clicks have energy distributed between two main frequency bands with the higher frequencies delayed in time by 5-20 micros. Signal syntheses using a multiple chirp model based on these observations are able to reproduce much of the spectral variation seen in earlier studies on natural dolphin echolocation pulses. Six synthetic signals are generated and used to drive the dolphin based sonar (DBS) developed through the Biosonar Program office at the SPAWAR Systems Center, San Diego, CA. Analyses of the detailed echo structure for these pulses ensonifying two solid copper spherical targets indicate differences in discriminatory potential between the signals. It is suggested that target discrimination could be improved through the transmission of a signal packet in which the chirp structure is varied between pulses. Evidence that dolphins may use such a strategy themselves comes from observations of variations in the transmissions of dolphins carrying out target detection and identification tasks.

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To date most sonars use narrow band pulses and often only the echo envelope is used for object detection and classification. This paper considers the advantages afforded by bio-inspired sonar for object identification and classification through the analysis and the understanding of the broadband echo structure. Using the biomimetic dolphin based sonar system in conjunction with bio-inspired pulses developed from observations of bottlenose dolphins performing object identification tasks, results are presented from experiments carried out in a wave tank and harbor. In these experiments responses of various targets to two different bio-inspired signals are measured and analyzed. The differences in response demonstrate the strong dependency between signal design and echo interpretation. In the simulations and empirical data, the resonance phenomena of these targets cause strong notches and peaks in the echo spectra. With precision in the localization of these peaks and dips of around 1 kHz, the locations are very stable for broadside insonification of the targets and they can be used as features for classification. This leads to the proposal of a broadband classifier which operates by extracting the notch positions in the target echo spectra.

MIMO (Multiple-Input Multiple-Output) sonar systems offer new perspectives for area surveillance especially in complex environments where strong multi-path and dense clutter can become very challenging. This paper proposes a MIMO sonar system based scheme to tackle the difficult problem of harbour surveillance. An emphasis is put on recognition and tracking on low profile mid-water targets. A MIMO simulator which can compute synthetic raw data for any transmitter/receiver pair in multipath and cluttered environment is presented. Moving targets such as boats or AUVs (Autonomous Underwater Vehicle) can also be introduced into the environment. The present paper proposes two radically different methods for the underwater target tracking problem in complex environment: a digital tracker and an analog tracker. On the digital side, an implementation of the recently developed HISP filter (Hypothesised filter for Independent Stochastic Populations) is presented. This filter enables robust multi-object tracking as well as track classification capabilities without the use of heuristics. While digital filters track the objects after processing in the digital domain, an analog filter based on acoustical time reversal techniques enable to track an underwater target using MIMO architecture capabilities is also presented. The proposed modified time reversal technique matches the prediction / data update steps of a traditional tracking filter.