Impact of temporal Doppler on synthetic aperture sonar imagery.

Synthetic Aperture Sonar (SAS) coherently processes the acoustic data acquired along a linear trajectory. The imaging process is in essence an inverse problem where the reflectivity of the seafloor has to be estimated. Several imaging algorithms have been proposed over the years including back-projection algorithms. One commonly assumed hypothesis, however, is that the antenna is motionless during transmission and reception. This hypothesis is known as the start-stop assumption. This paper questions the validity of this assumption, and proposes a full derivation of the SAS processing taking into account the vehicle motion by using the Lorentz transformation. The cell migration for the SAS system is computed and the validity limit of the stop-start assumption depending on the SAS system parameters is derived. Numerical examples of start-stop assumption violations are given and the Doppler cell migration correction on real SAS data are presented and discussed.

Analysis and classification of broadband echoes using bio-inspired dolphin pulses.

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.

Bio-inspired wideband sonar signals based on observations of the bottlenose dolphin (Tursiops truncatus).

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.

The fusion of large scale classified side-scan sonar image mosaics.

This paper presents a unified framework for the creation of classified maps of the seafloor from sonar imagery. Significant challenges in photometric correction, classification, navigation and registration, and image fusion are addressed. The techniques described are directly applicable to a range of remote sensing problems. Recent advances in side-scan data correction are incorporated to compensate for the sonar beam pattern and motion of the acquisition platform. The corrected images are segmented using pixel-based textural features and standard classifiers. In parallel, the navigation of the sonar device is processed using Kalman filtering techniques. A simultaneous localization and mapping framework is adopted to improve the navigation accuracy and produce georeferenced mosaics of the segmented side-scan data. These are fused within a Markovian framework and two fusion models are presented. The first uses a voting scheme regularized by an isotropic Markov random field and is applicable when the reliability of each information source is unknown. The Markov model is also used to inpaint regions where no final classification decision can be reached using pixel level fusion. The second model formally introduces the reliability of each information source into a probabilistic model. Evaluation of the two models using both synthetic images and real data from a large scale survey shows significant quantitative and qualitative improvement using the fusion approach.

Short-time fractional Fourier methods for the time-frequency representation of chirp signals.

The fractional Fourier transform (FrFT) provides a valuable tool for the analysis of linear chirp signals. This paper develops two short-time FrFT variants which are suited to the analysis of multicomponent and nonlinear chirp signals. Outputs have similar properties to the short-time Fourier transform (STFT) but show improved time-frequency resolution. The FrFT is a parameterized transform with parameter, a, related to chirp rate. The two short-time implementations differ in how the value of a is chosen. In the first, a global optimization procedure selects one value of a with reference to the entire signal. In the second, a values are selected independently for each windowed section. Comparative variance measures based on the Gaussian function are given and are shown to be consistent with the uncertainty principle in fractional domains. For appropriately chosen FrFT orders, the derived fractional domain uncertainty relationship is minimized for Gaussian windowed linear chirp signals. The two short-time FrFT algorithms have complementary strengths demonstrated by time-frequency representations for a multicomponent bat chirp, a highly nonlinear quadratic chirp, and an output pulse from a finite-difference sonar model with dispersive change. These representations illustrate the improvements obtained in using FrFT based algorithms compared to the STFT.