Research on the Relative Positions-Constrained Pattern Matching Method for Underwater Gravity-Aided Inertial Navigation

Database-referenced navigation (DBRN) using geophysical information is often implemented on autonomous underwater vehicles (AUVs) to correct the positional errors of the inertial navigation system (INS). The matching algorithm is a pivotal technique in DBRN. However, it is impossible to completely eliminate mismatches in practical application. Therefore, it is necessary to perform a mismatch detection method on the outputs of DBRN. In this paper, we propose a real-time triple constraint mismatch detection method. The proposed detection method is divided into three modules: the model fitting detection module, the spatial structure detection module, and the distance ratio detection module. In the model fitting detection module, the navigation characteristics of AUVs are used to select the fitting model. In the spatial structure detection module, the proposed method performs the mismatch detection based on the affine transformation relationship between the INS-indicated trajectory and the corresponding matched trajectory. In the distance ratio detection module, we derive the distance ratio constraint between the INS-indicated trajectory and the corresponding matched trajectory. Simulations based on an actual geomagnetic anomaly base map have been performed for the validation of the proposed method.

Section: The Real-time Triple Constraint Mismatch Detection Methodsmentioning

confidence: 99%

A Real-Time Mismatch Detection Method for Underwater Database-Referenced Navigation

Dai

Liu

Guo

2019

“…No matter which method is adopted, the core concept of the gravity anomaly matching algorithm is based on the fact that the gravity anomaly in navigation regions of the underwater submarine has various characteristics, and different characteristics alter gravity matching navigation accuracy. Thus, it is necessary to construct a proper parameter that evaluates characteristics of the gravity anomaly zone and analyzes the influence of characteristic parameters on the location accuracy of gravity matching [ 30 , 31 ].…”

Section: Principles Of Gravity-aided Navigation and Characteristicmentioning

confidence: 99%

Characteristics of Marine Gravity Anomaly Reference Maps and Accuracy Analysis of Gravity Matching-Aided Navigation

Wang

Chai

et al. 2017

Self Cite

The variation of a marine gravity anomaly reference map is one of the important factors that affect the location accuracy of INS/Gravity integrated navigation systems in underwater navigation. In this study, based on marine gravity anomaly reference maps, new characteristic parameters of the gravity anomaly were constructed. Those characteristic values were calculated for 13 zones (105°–145° E, 0°–40° N) in the Western Pacific area, and simulation experiments of gravity matching-aided navigation were run. The influence of gravity variations on the accuracy of gravity matching-aided navigation was analyzed, and location accuracy of gravity matching in different zones was determined. Studies indicate that the new parameters may better characterize the marine gravity anomaly. Given the precision of current gravimeters and the resolution and accuracy of reference maps, the location accuracy of gravity matching in China’s Western Pacific area is ~1.0–4.0 nautical miles (n miles). In particular, accuracy in regions around the South China Sea and Sulu Sea was the highest, better than 1.5 n miles. The gravity characteristic parameters identified herein and characteristic values calculated in various zones provide a reference for the selection of navigation area and planning of sailing routes under conditions requiring certain navigational accuracy.

“…Gravity matching-aided navigation primarily uses a variety of methods to compare the gravity values obtained using marine gravimeters and those stored in reference maps, thereby determining the optimal matching point according to the degree of fit between the two types of gravity values. Algorithms of gravity matching-aided navigation can largely be divided into two types, i.e., related matching algorithms represented by terrain contour matching (TERCOM) [ 18 , 19 ] and interactive closest contour point (ICCP) [ 20 ], and multi-model Kalman filtering algorithms represented by the Sandia inertial terrain-aided navigation (SITAN) [ 21 , 22 ]. There are other algorithms, such as neural networks and particle filtering [ 23 , 24 , 25 ].…”

Section: Principles Of Igns and Variation Characteristics Of Gravimentioning

confidence: 99%

Location Accuracy of INS/Gravity-Integrated Navigation System on the Basis of Ocean Experiment and Simulation

Wang

Chai

et al. 2017

Self Cite

An experiment comparing the location accuracy of gravity matching-aided navigation in the ocean and simulation is very important to evaluate the feasibility and the performance of an INS/gravity-integrated navigation system (IGNS) in underwater navigation. Based on a 1′ × 1′ marine gravity anomaly reference map and multi-model adaptive Kalman filtering algorithm, a matching location experiment of IGNS was conducted using data obtained using marine gravimeter. The location accuracy under actual ocean conditions was 2.83 nautical miles (n miles). Several groups of simulated data of marine gravity anomalies were obtained by establishing normally distributed random error Nfalse(u,σ2false) with varying mean u and noise variance σ2. Thereafter, the matching location of IGNS was simulated. The results show that the changes in u had little effect on the location accuracy. However, an increase in σ2 resulted in a significant decrease in the location accuracy. A comparison between the actual ocean experiment and the simulation along the same route demonstrated the effectiveness of the proposed simulation method and quantitative analysis results. In addition, given the gravimeter (1–2 mGal accuracy) and the reference map (resolution 1′ × 1′; accuracy 3–8 mGal), location accuracy of IGNS was up to reach ~1.0–3.0 n miles in the South China Sea.