UACE2023: HIGH DUTY CYCLE SONAR TRACKING PERFORMANCE AS A FUNCTION OF COHERENT PROCESSING INTERVAL FOR LCAS’15 DATA



  • Session: 11. Large Time-Bandwidth acoustic signals for target detection and tracking
    Organiser(s): Tesei Alessandra
  • Lecture: HIGH DUTY CYCLE SONAR TRACKING PERFORMANCE AS A FUNCTION OF COHERENT PROCESSING INTERVAL FOR LCAS’15 DATA [invited]
    Paper ID: 989
    Author(s): Grimmett Doug, Itschner Jonathan, Abraham Doug, Mazutti Leonardo
    Presenter: Grimmett Doug
    Presentation type: oral
    Abstract: High Duty Cycle (HDC) sonar transmits with nearly 100% duty cycle. For LFM waveforms, this yields very large time-bandwidth products, with signal bandwidth swept over the entire transmission’s ping repetition interval (PRI). In receive processing, the PRI may be split up into shorter coherent processing intervals (CPIs), providing multiple detection opportunities per PRI. The potential advantage is an increased number of near continuous detection opportunities, leading to improved target localization, tracking, and classification, due to there being less time lapse between measurement scans. The corresponding disadvantage is that probability of detection and ranging accuracy may be lower per individual CPI detection opportunity. The choice of CPI for HDC sonar will influence detection and tracking performance. \n\nIn this paper, the choice of CPI is evaluated using sonar data collected during the Littoral Continuous Active Sonar 2015 (LCAS’15) seatrial for a non-maneuvering surrogate target. A processing chain, including target tracker, is used to evaluate performance as a function of CPI. Typical track initiation algorithms (TIA) require setting parameters like SNR threshold and an M-of-N observation sequence to control the false track rates typical of clutter-rich environments. Previous analysis has been performed with constant tracker parameters across different CPIs, but here, we follow a more fair comparison approach by optimizing the tracker initiation parameters for each individual CPI case. Processing metrics such as signal-to-noise ratio, probability of detection, and false alarm rate, as well as tracking metrics such as track-hold time, false track rate, and localization accuracy are reported. The relative advantages and disadvantages of reducing CPI are analyzed and explained for this dataset using these metrics.\n\n\n\n\n\n\n\n\n\n\n\n\n
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  • Corresponding author: Mr Grimmett Doug
    Affiliation: Naval Information Warfare Center Pacific
    Country: United States
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