Multi-waveform active sonar tracking

2006 9th International Conference on Information Fusion

Carthel

et al. 2006

Self Cite

Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. NURC also provides services to other sponsors through the Supplementary Work Program (SWP). These activities are undertaken to accelerate implementation of new military capabilities for NATO and the Nations, to provide assistance to the Nations, and to ensure that the Centre's maritime capabilities are sustained in a fully productive and economic manner. Examples of supplementary work include ship chartering, military experimentation, collaborative work with or services to Nations and industry.NURC's plans and operations are extensively and regularly reviewed by outside bodies including peer review of the research, independent national expert oversight, review of proposed deliverables by military user authorities, and independent business process certification. The Scientific Committee of National Representatives, membership of which is open to all NATO nations, provides scientific guidance to the Centre and the Supreme Allied Commander Transformation.Copyright © NATO Undersea Research Centre 2005. NATO member nations have unlimited rights to use, modify, reproduce, release, perform, display or disclose these materials, and to authorize others to do so for government purposes. Any reproductions marked with this legend must also reproduce these markings. All other rights and uses except those permitted by copyright law are reserved by the copyright owner. NOTE:

Section: Target Tracking At Nurcmentioning

confidence: 99%

“…A detailed description of the multi-hypothesis tracker is in [9]. The multi-hypothesis tracker uses the same kinematic and measurement models, association gate criterion, nonlinear kinematic filter, and track-length classifier as the baseline tracker.…”

Section: Multi-hypothesis Tracker (Mht)mentioning

confidence: 99%

Benchmark Analysis of NURC Multistatic Tracking Capability

Gerard

2006 9th International Conference on Information Fusion

Carthel

et al. 2006

Self Cite

“…In particular, we will examine multi-stage processing of simulated multistatic sonar data made available to the ISIF Multi-Static Tracking Working Group (MSTWG) by METRON [7]. This work will require nonlinear extensions to the ML processing stage, and relies on precise transformation of bistatic sonar measurement errors to Cartesian coordinates [8][9]. Illustrations of preliminary results on the METRON datasets (obtained with the MHT processing architecture) are in Annex A.…”

Section: Conclusion and Further Extensionsmentioning

confidence: 99%

An ML-MHT approach to tracking dim targets in large sensor networks

2010 13th International Conference on Information Fusion

Carthel

2010

-Poor individual sensor performance as well as a large number of sensor scans per time interval are two challenges for multi-target tracking is large sensor networks. We introduce a two-stage processing scheme (ML-MHT) to address the former issue, and another to address the latter issue (MHT 2 ). We consider as well the combination of these two techniques (ML-MHT 2 ). Simulation results are encouraging. Future work will include application of these techniques to more challenging multi-sensor datasets characterized by extremely poor detection and localization performance.

“…In recent work [3], [4], localization errors for bistatic and quasi-monostatic contact localization accuracy were derived as a function of the source-target-receiver geometry and assumed error statistics for source and receiver locations, sound speed, time, bearing, and array heading measurements. This study illustrated that the impact of measurement errors on localization accuracy depends highly on the source-target-receiver geometry.…”

Section: A Measurement Model and Localization Accuraciesmentioning

confidence: 99%

“…This study illustrated that the impact of measurement errors on localization accuracy depends highly on the source-target-receiver geometry. Due to space limitations we omit the lengthy equations showing the relations between the errors mentioned above and the components of covariance matrices, and refer the interested reader to the related publications [3] and [4]. Coraluppi has described the measurement errors and, more important, the measurement error covariances, as a function of the fundamental system errors in angle, observation time, array orientation, speed of sound and source receiver locations.…”

Section: A Measurement Model and Localization Accuraciesmentioning

confidence: 99%

Multistatic Sensor Placement: A Tracking Approach

Erdinc

Willett

2006 9th International Conference on Information Fusion

2006

Self Cite

Active sonar tracking using measurements from multistatic sensors has shown promise: there are benefits in terms of robustness, complementarity (covariance-ellipse intersection) and of course simply due to the increased probability of detection that naturally accrues from a well-designed data fusion system. It is not always clear what the placement of the sources and receivers that gives the best fused measurement covariance for any target -or at least for any target that is of interest -might be. In this paper, we investigate the problem as one of global optimization, in which the objective is to maximize the information provided to the tracker.We assume that the number of sensors is given, so that the optimization is done in a continuous space. The strong variability of target strength as a function of aspect is integral to the cost function we optimize. Doppler information is not discarded when constant frequency (Doppler-sensitive) waveforms are available. The optimal placements that result are consistent with our intuition, suggesting that our placement strategy may provide a useful tool in more complex scenarios where intuition is challenged. Index TermsMultistatic active sonar, optimization, sensor placement, sensor management, information gain, anti-submarine warfare, ASW.