A Review of Key Technologies in Gravity Matching Navigation

The passive nature of gravity matching navigation, along with its concealment and freedom from error accumulation over time, is essential for reducing inertial navigation system (INS) errors and enabling high-precision autonomous underwater positioning. The current paper provides a systematic review of major technologies in the field, including the development of underwater gravimeters, construction of gravity reference maps, suitable area selection, optimization of matching algorithms, gravity-inertial integrated navigation, and path planning. We discuss hardware developments, including classical sensors, gradiometers, and quantum sensors, as well as methodological concepts such as multi-source sensor data fusion, intelligent area selection, algorithm optimizations, connections between multiple filters, and intelligent trajectory design. Despite a relatively well-developed technical infrastructure, several bottlenecks remain, including the low engineering maturity of high-end hardware, poor algorithmic performance under extreme conditions, over-reliance on simulation, and weak module integration. Future research should focus on hardware miniaturization, cross-domain intelligent adaptive algorithms, multi-condition real-world validation, and the transition from loosely coupled to tightly coupled architectures to achieve improved accuracy and robustness.