E. Hanusa

University of Washington Seattle, Seattle, Washington, United States

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Publications (13)4.63 Total impact

  • E. Hanusa, D.W. Krout, M.R. Gupta
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    ABSTRACT: This paper presents results of a clustering-based preprocessing step for multistatic tracking, evaluated on the PACsim dataset, a simulated multistatic active sonar dataset. The clustering step uses a flexible likelihood-based similarity calculation which allows for the incorporation of any available features. In this work, we present results using target strength (estimated from signal-to-noise ratio) and Doppler measurements. Results show that this approach performs well on dim targets in high clutter environments.
    Information Fusion (FUSION), 2013 16th International Conference on; 01/2013
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    ABSTRACT: Recently a data set was collected using an imaging sonar of a non-stationary underwater object. This paper presents the image processing algorithms as well as the tracking algorithms used to take the imaging sonar data and track a non-stationary underwater extended object. The tracking results will be presented in a geo-referenced image frame with the use of GPS and inertial sensors. Future work with this data set will include feature extraction and object classification using the imaging sonar data.
    Information Fusion (FUSION), 2012 15th International Conference on; 01/2012
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    ABSTRACT: We present an overview of the data collection and transcription eorts for the COnversational Speech In Noisy Environments (COSINE) corpus. The corpus is a set of multi-party conversations recorded in real world environments, with background noise, that can be used to train noise-robust speech recognition systems or develop speech de-noising algorithms. We explain the motivation for creating such a corpus, and describe the resulting audio recordings and transcriptions that comprise the corpus. These high quality recordings were captured in-situ on a custom wearable recording system, whose design and construction is also described. On separate synchronized audio channels, seven-channel audio is captured with a 4-channel far-eld microphone array, along with a close-talking, a monophonic far-eld, and a throat microphone. This corpus thus creates many possibilities for speech algorithm research.
    Computer Speech & Language. 01/2012; 26:52-66.
  • E. Hanusa, D.W. Krout
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    ABSTRACT: This paper presents tracking results on the PACsim data set using a framework based on the JPDA algorithm with a posterior distribution preprocessing step. The dataset is a multistatic simulation designed to approximate real-life data. In this paper, we extend the posterior distribution preprocessing technique to include feature data and compare tracking results with and without feature information. Results show that the inclusion of feature data in the preprocessing stage can improve tracking performance. This work also explores the benefits of more extensive parameter tuning for the harder tracking scenarios included in the dataset.
    Information Fusion (FUSION), 2012 15th International Conference on; 01/2012
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    ABSTRACT: Recently, researchers at the Applied Physics Laboratory at the University of Washington collected a unique dataset by suspending two cameras, one infrared and one electro-optical, from a balloon. This apparatus was then used to image objects drifting on the surface of Lake Washington. The authors took that data and built a processing stream to track the movements of those drifting surface objects.
    Oceans, 2012; 01/2012
  • E. Hanusa, M.R. Gupta, D.W. Krout
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    ABSTRACT: This paper presents the results of using a likelihood-based clustering step before tracking on a multistatic sonar step. The likelihood-based clustering appropriately models the measurement noise and allows for the incorporation of features. The clustering step also allows for the rejection of clutter and fusion of the contact measurements within a cluster. After clustering, fusion and classification, the tracking results are improved over previous preprocessing methods. Results are shown for the three scenarios in the PACSim dataset.
    Oceans, 2012; 01/2012
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    E. Hanusa, D. Krout, M.R. Gupta
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    ABSTRACT: We implement and evaluate a likelihood-based method to cluster contacts in a multistatic active sonar setting. The underlying assumption is that a true contact will be detected by multiple receivers and any aspect-dependent feature must be consistent across all contacts in a cluster. Contacts which are contained in the same cluster can be appropriately fused and passed into a tracker. Clutter contacts detected are rejected if they are not in a cluster with any other possible objects. The use of the aspect dependent features Doppler and target strength allows for improved rejection of clutter. We show that clutter can be rejected with minimal false negatives.
    Information Fusion (FUSION), 2011 Proceedings of the 14th International Conference on; 08/2011
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    Evan Hanusa, David Krout
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    ABSTRACT: This paper presents a method for using information from tracking to improve the results of contact classification. An Extended Kalman Filter is used to predict the target's state (position and velocity) at the current time. The predicted state is used to estimate the target's aspect and heading. The estimate is used in tandem with aspect-dependent features (Doppler and target strength) to classify contacts as targets or clutter. Results on three simulated datasets show that using the velocity estimate and the covariance from the track state results in increased classification accuracy.
    01/2011;
  • D.W. Krout, G. Okopal, E. Hanusa
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    ABSTRACT: Recently a data set was collected that includes video data and imaging sonar data in the underwater environment. This data set provides a unique example of a data fusion problem that is not commonly found in the underwater environment. This paper presents the fusion of data from a video camera and an imaging sonar, which is then processed by a target tracking algorithm.
    Information Fusion (FUSION), 2011 Proceedings of the 14th International Conference on; 01/2011
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    ABSTRACT: This paper presents approaches for incorporating classification information into target tracking algorithms, specifically in a multistatic active sonar context. In addition, this paper describes the framework designed for simulation and classification of return time series from simulated targets and clutter in a realistic underwater environment. The simulated target and clutter returns are integrated into an existing contact-based tracking dataset (TNO Blind dataset) for which time series are unavailable. Simulations compare the integrating classification of contacts at different stages of tracking algorithms. Results show improvements in some tracking metrics with no degradation of the others.
    OCEANS 2010; 10/2010
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    D.W. Krout, E. Hanusa
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    ABSTRACT: This paper presents tracking results on the Metron data set using the JPDA algorithm and a preprocessing likelihood surface formulation. The Metron data set is a simulated data set and is designed to be very difficult with large bearing and range errors which leads to high localization error for true detections. There are also significant amounts of clutter. Results using other data association algorithms such as the PDA, PDAFAI, and PDAFAIwTS were not good, which led to the use of a likelihood surface. The preprocessing step using the likelihood surface is key for achieving reasonable results. For the baseline tracking scenario where the truth is known, the results were encouraging. Extending this technique to include acoustic modeling and Doppler information will be topics of future research.
    Information Fusion (FUSION), 2010 13th Conference on; 08/2010
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    E. Hanusa, D. Krout, M.R. Gupta
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    ABSTRACT: We implement and evaluate a method infer position from Doppler measurements in a multistatic sonar scenario and present a likelihood approach for doing so. Doppler measurements are used to create likelihood surfaces for each of the transmitter-receiver pairs. The likelihood surfaces are combined and can then be used as-is or combined with additional position measurements. The final likelihood surface is usable in a Bayesian-style tracker or can be used to estimate position of a contact for use in a contact-based tracker. We show how the estimate improves with the addition of multiple receivers and show how the use of Doppler information can improve tracking results.
    Information Fusion (FUSION), 2010 13th Conference on; 08/2010
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    ABSTRACT: We present an overview of the data collection and transcription efforts for the COnversational Speech In Noisy Environments (CO- SINE) corpus. The corpus is a set of multi-party conversations recorded in real world environments with background noise that can be used to train noise-robust speech recognition systems. We explain the motivation for creating such a corpus and describe the resulting audio recordings and transcriptions that comprise the corpus. These recordings include a 4-channel array and close-talking, far-field, and throat microphones on separate synchronized channels, allowing for unique algorithm research.
    Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009, 19-24 April 2009, Taipei, Taiwan; 01/2009