“…In the past decades, gravity/gravity gradient aided navigation has been developed for underwater passive navigation systems to limit the INS error accumulation [ 1 , 2 , 3 , 4 , 5 , 6 ]. Several methods were explored for gravity matching aided navigation (GMAN).…”
Simulation tests were accomplished in this paper to evaluate the performance of gravity matching aided navigation (GMAN). Four essential factors were focused in this study to quantitatively evaluate the performance: gravity database (DB) resolution, fitting degree of gravity measurements, number of samples in matching, and gravity changes in the matching area. Marine gravity anomaly DB derived from satellite altimetry was employed. Actual dynamic gravimetry accuracy and operating conditions were referenced to design the simulation parameters. The results verified that the improvement of DB resolution, gravimetry accuracy, number of measurement samples, or gravity changes in the matching area generally led to higher positioning accuracies, while the effects of them were different and interrelated. Moreover, three typical positioning accuracy targets of GMAN were proposed, and the conditions to achieve these targets were concluded based on the analysis of several different system requirements. Finally, various approaches were provided to improve the positioning accuracy of GMAN.
“…In the past decades, gravity/gravity gradient aided navigation has been developed for underwater passive navigation systems to limit the INS error accumulation [ 1 , 2 , 3 , 4 , 5 , 6 ]. Several methods were explored for gravity matching aided navigation (GMAN).…”
Simulation tests were accomplished in this paper to evaluate the performance of gravity matching aided navigation (GMAN). Four essential factors were focused in this study to quantitatively evaluate the performance: gravity database (DB) resolution, fitting degree of gravity measurements, number of samples in matching, and gravity changes in the matching area. Marine gravity anomaly DB derived from satellite altimetry was employed. Actual dynamic gravimetry accuracy and operating conditions were referenced to design the simulation parameters. The results verified that the improvement of DB resolution, gravimetry accuracy, number of measurement samples, or gravity changes in the matching area generally led to higher positioning accuracies, while the effects of them were different and interrelated. Moreover, three typical positioning accuracy targets of GMAN were proposed, and the conditions to achieve these targets were concluded based on the analysis of several different system requirements. Finally, various approaches were provided to improve the positioning accuracy of GMAN.
“…However, the navigation errors of INS increase with time during extended AUV missions. One method for correcting such errors without compromising the AUV mission is by use of underwater gravity aided navigation (GAN) [1–13]. Considering the covertness of an AUV, gravimetry is not easily detected and interfered with, unlike GPS, radar, laser and sonar.…”
“…Gravity-aided navigation is stable and passive and thus is appropriate for covert underwater navigation. In the past few years, gravity/gravity gradient-aided underwater passive navigation systems have been established on AUVs or submarines to limit INS error accumulation (Affleck and Jircitano, 1990; Goldstein and Brett, 1998; Hays, 2002; Jircitano et al, 1990; Moryl et al, 1998; Rice et al, 2000; Rice et al, 2004; Vajda and Zorn, 1998; Wang and Bian, 2008). Gravimeters and gradiometers were adopted to compensate the INS (Jekeli, 2006; Moody and Paik, 2004).…”
A Relative Positions-Constrained pattern Matching (RPCM) method for underwater gravityaided inertial navigation is presented in this paper. In this method the gravity patterns are constructed based on the relative positions of points in a trajectory, which are calculated by Inertial Navigation System (INS) indications. In these patterns the accumulated errors of INS indicated positions are cancelled and removed. Thus the new constructed gravity patterns are more accurate and reliable while the process of matching can be constrained, and the probability of mismatching also can be reduced. Two gravity anomaly maps in the South China Sea were chosen to construct a simulation test. Simulation results show that with this RPCM method, the shape of the trajectory in gravity-aided navigation is not as restricted as that in traditional Terrain Contour Matching (TERCOM) algorithms. Moreover, the performance included matching success rates and position accuracies are highly improved in the RPCM method, especially for the trajectories that are not in straight lines. Thus the proposed method is effective and suitable for practical navigation.
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