With the expansion of the exploration scope of underwater vehicles and the improvement of their safety requirements, integrated navigation under passive conditions has become a hot topic in the field of navigation. Due to the stability and detectability of the Earth’s gravity field, the use of a matching result for external correction of inertial navigation systems (INSs) can be effective. For practical navigation applications, an inertial gravity matching integrated navigation algorithm must be designed for real-time applicability, diversified output information capability, and anti-interference capability. In this paper, an INS/gravity matching (INS-GM) integrated navigation algorithm is improved to extract the information of gravity fields in real time and correct the navigation results, and a robust integrated algorithm is proposed. Through two-hierarchy filtering, correction of the gravity field to the carrier position and of the integrated navigation system is obtained. According to the first-hierarchy filtering noise characteristics of gravity matching, the robustness of the algorithm to a complex environment is improved by second-hierarchy filtering. The ocean experiment data processing results show that the algorithm can effectively handle a certain degree of initial error, and an integrated navigation accuracy of 205 m is achieved in a good experimental environment. In the case of severe test conditions, the accuracy of the robust integrated navigation algorithm is 72% higher than that of the ordinary navigation algorithm, and it has a strong anti-jamming ability, which can meet the requirements of marine inertial gravity matching integrated navigation tasks.

Compensation of gravity disturbance can improve the precision of inertial navigation, but the effect of compensation will decrease due to the accelerometer bias, and estimation of the accelerometer bias is a crucial issue in gravity disturbance compensation. This paper first investigates the effect of accelerometer bias on gravity disturbance compensation, and the situation in which the accelerometer bias should be estimated is established. The accelerometer bias is estimated from the gravity vector measurement, and a model of measurement noise in gravity vector measurement is built. Based on this model, accelerometer bias is separated from the gravity vector measurement error by the method of least squares. Horizontal gravity disturbances are calculated through EGM2008 spherical harmonic model to build the simulation scene, and the simulation results indicate that precise estimations of the accelerometer bias can be obtained with the proposed method.

Due to the errors of the accelerometer and gyroscope, the position and the velocity calculated by the inertial navigation system (INS) are divergent with time. We can normally estimate and compensate the errors of the INS using the underwater sensors. However, the underwater sensors such as ultrashort baseline (USBL) acoustic positioning system and Doppler velocity log (DVL) are challenged by the complex environment, which affects the reliability and the accuracy of data processing. From the gravimetry error equation, the horizontal position errors have little influence on the underwater gravimetry. Observability analysis indicates that the velocity error and the position error can be well estimated on the condition of only positional observations in the Kalman filter. Based on these, we proposed a novel method using the INS and depth gauge (DG) based on trajectory constraint without USBL and DVL. In this method, we considered to fit the track of the gravimeter to a straight line because the gravimeter maintains uniform motion in the measuring line and take the fit line and the depth measured by the DG as the observations to correct the errors of the INS. We constructed an underwater experiment in 2019 to test the novel method. The test results showed a repeatability from 1.24 to 2.03 mGal for the space resolution of 200 m. The new method can acquire a good accuracy and can be applied to the gravimetry data processing.

Underwater gravity information plays a major role in deepwater oil and gas exploration. To realize underwater dynamic gravimetry, we have developed a strapdown gravimeter mounted in a pressure capsule for adaption to the underwater environment and we adopted a two-stage towed underwater gravimetry scheme. An improved strapdown gravimeter and other underwater sensors were installed in a towed vessel to form an underwater dynamic gravimetry system. Because the global navigation satellite system cannot be used for underwater dynamic gravimetry, we developed a new method based on underwater multisensor integrated navigation, in which a federal Kalman filter was applied for error estimation. This new method allowed us to obtain the accurate attitude, velocity, and position necessary for gravity estimation. In addition, the gravity data can then be extracted from the noisy data through finite impulse response low-pass filtering. We acquired the underwater gravity data at a depth of 300 m to test the validity of the new method and evaluate the accuracy of the underwater gravity system. The results indicated a repeatability from 0.85 to 0.96 mGal at a half wavelength of approximately 0.2 km and also indicated good consistency with the marine gravity data.

To deceive Inertial Navigation System(INS)/Global Navigation Satellite System(GNSS) integrated navigation terminals, the entry point is still to inject GNSS spoofing signals to the target system. However, the spoofing control strategy in integrated navigation mode for particular tasks such as fixed-point capture or directional drive needs further research. Whether applying GNSS spoofing attacks or not, the Kalman filter correction gain matrix element in the tightly coupled navigation system always maintains its stability, which gives us valuable clues to develop an effective spoofing attack. On this basis, this article focuses on the feasibility and operability of spoofing attacks under tightly coupled navigation conditions and innovatively proposes a spoofing control strategy that can achieve accurate position offsets: Specific spoofing signals are implanted to the target tightly coupled navigation terminal at the beginning of the spoofing attack. The amounts of pseudo-range spoofing signals corresponding to different satellites are respectively the projections of the position increments to be deceived on the sight vector of the integrated navigation terminal to each satellite. Simulation experiments and tightly coupled navigation terminal experiments verify the correctness and effectiveness of the spoofing control strategy.