Shari Matzner

Frequency domain tracking of passive vessel harmonics.

This paper presents a method for passive acoustic detection and tracking of small vessels in noisy, shallow water marine environments. Passive spectra of boats include broadband noise as well as tones that are harmonics of the engine speed and shaft/propeller rotation. Past work suggests that the location in frequency and the relative amplitudes of these harmonics can be used to determine specific characteristics of the vessel such as the number of blades on the propeller and engine type/speed. However, the low signal to noise ratio of quiet targets and Doppler shifts incurred because of source and receiver motion complicate the identification of these tones in the lofargram. To address this issue, a combined detection and tracking approach is proposed in which intermittent and wandering harmonic content is tracked with a multi‐dimensional Kalman filter. Results from recorded passive signatures from several classes of vessels in marine and freshwater environments in the Pacific Northwest are presented and...

Adaptive critic learning with fuzzy utility

Adaptive critic methods, which approximate dynamic programming, have been used successfully for solving optimal control problems. The adaptive critic learning algorithm optimizes a secondary utility function that is the sum of the present and all future primary utility. The primary utility function measures the instantaneous cost incurred for the last action taken and the resulting state. The motivation for using a fuzzy primary utility function comes from the set of control problems for which there is only a qualitative definition of performance - for example, success or failure. Previous work in applying adaptive critic methods to this type of problem showed that a crisp definition of success resulted in solutions that met the control objective, but in an undesirable manner. An appropriate fuzzy utility function, on the other hand, is able to generate the optimal solution. Another motivation for incorporating fuzzy techniques into the utility function is to overcome measurement noise. Measurement noise has a significant adverse effect on the reliability and speed of adaptive critic learning; by incorporating fuzzy sets into the utility function, the effect of the noise can be mitigated.

Frequency domain feature extraction from synthetic aperture radar data

Most feature recognition and classification algorithms for synthetic aperture radar (SAR) are done in the image domain, and thus do not explicitly exploit the scattering physics underlying the data. Feature extraction in the phase domain is based on electromagnetic scattering models which describe the sensor response to scene features. This idea of processing the SAR data using a filter matched to the phase history signature of a feature was introduced by Franceschetti (1997). Here, we extend the original concept for processing the raw signal to processing the spotlight mode SAR signal. We use a sensor model based on an experimental airborne SAR developed by MIT Lincoln Laboratory, the Lincoln Multimission ISR Testbed (LiMIT). To demonstrate the concept, line feature filters are applied to a simulation of a building from the LiMIT dataset.

Multipath return for radar targets over a rough surface

A scattering formulation is described here which can be used to understand and predict the electromagnetic scattering from a target positioned over a (potentially) rough interface. It has application to the evaluation of radar performance in the presence of multipath

Monitoring and Mitigation Alternatives for Protection of North Atlantic Right Whales during Offshore Wind Farm Installation

Progress report on defining and determining monitoring and mitigation measures for protecting North Atlantic Right Whales from the effects of pile driving and other activities associated with installation of offshore wind farms.

Marine Animal Alert System -- Task 2.1.5.3: Development of Monitoring Technologies -- FY 2011 Progress Report

The Marine Animal Alert System (MAAS) in development by the Pacific Northwest National Laboratory is focused on providing elements of compliance monitoring to support deployment of marine hydrokinetic energy devices. An initial focus is prototype tidal turbines to be deployed in Puget Sound in Washington State. The MAAS will help manage the risk of injury or mortality to marine animals from blade strike or contact with tidal turbines. In particular, development has focused on detection, classification, and localization of listed Southern Resident killer whales within 200 m of prototype turbines using both active and passive acoustic approaches. At the close of FY 2011, a passive acoustic system consisting of a pair of four-element star arrays and parallel processing of eight channels of acoustic receptions has been designed and built. Field tests of the prototype system are scheduled for the fourth quarter of calendar year 2011. Field deployment and testing of the passive acoustic prototype is scheduled for the first quarter of FY 2012. The design of an active acoustic system that could be built using commercially available off-the-shelf components from active acoustic system vendors is also in the final stages of design and specification.