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Sensors (Basel) ; 23(2)2023 Jan 09.
Article in English | MEDLINE | ID: mdl-36679556

ABSTRACT

This paper examines how tactical-grade Inertial Navigation Systems (INS), aided by Global Navigation Satellite System (GNSS) modules, vary from a survey-grade system in the bathymetric mapping in depths less than 20 m. The motivation stems from the advancements in sensor developments, measurement processing algorithms, and the proliferation of autonomous and uncrewed surface vehicles often seeking to use tactical-grade systems for high-quality bathymetric products. While the performance of survey-grade GNSS + INS is well-known to the hydrographic and marine science community, the performance and limitations of the tactical-grade micro-electro-mechanical system (MEMS) and tactical-grade fiber-optic-gyro (FOG) INS aided with GNSS require some study to answer the following questions: (1) How close or far is the tactical-grade GNSS + INS performance from the survey-grade systems? (2) For what survey order (IHO S-44 6th ed.) can a user deploy them? (3) Can we use them for navigation chart production? We attempt to answer these questions by deploying two tactical-grade GNSS + INS units (MEMS and FOG) and a survey-grade GNSS + INS on a survey boat. All systems collected data while operating a multibeam system with the lever-arm offsets accurately determined using a total station. The tactical-grade GNSS + INSs shared one pair of antennas for heading, while the survey-grade system used an independent antenna pair. We analyze the GNSS + INS results in sequence, examine the patch-test results, and the sensor-specific SBET-integrated bathymetric surfaces as metrics for determining the tactical-grade GNSS + INSs' reliability. In addition, we evaluate the multibeam's sounding uncertainties at different beam angles. The bathymetric surfaces using the tactical-grade navigation solutions are within 15 cm of the surface generated with the survey-grade solutions.


Subject(s)
Micro-Electrical-Mechanical Systems , Reproducibility of Results , Algorithms , Benchmarking , Fiber Optic Technology
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