# A Novel Hybrid Approach to Deal with DVL Malfunctions for Underwater Integrated Navigation Systems
## 1 Introduction  
With the increasing development of ocean exploration, underwater vehicles, including remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs), are employed to perform underwater tasks, such as bathymetric data collection and marine mining exploration [1; 2]. To successfully complete the scheduled tasks, an accurate and reliable navigation system is indispensable for underwater vehicles. Due to the advantages of high reliability and complete independence, the strapdown inertial navigation system (SINS) is commonly used for underwater navigation. The SINS provides velocity, position and attitude of the vehicle using the information obtained by the inertial measurement unit (IMU). The IMU is composed of gyroscopes and accelerometers to measure the angular rates and the specific forces respectively. The navigation errors of the SINS increase with time due to the inherent bias errors of gyroscopes and accelerometers [3; 4; 5]. Therefore, in order to improve the navigation performance, it is necessary to introduce auxiliary sensors to limit the error growth of the SINS. Now the integrated navigation system which consists of multiple navigation sensors is widely adoptedon underwater vehicles [6; 7; 8]. As a high-precision velocity measuring instrument, the Doppler velocity log (DVL) has become increasingly popular as the fundamental component of underwater integrated navigation systems [9; 10; 11; 12; 13]. The DVL provides the velocities relative to the seafloor or the current based on the Doppler effect [14]. By using a Kalman filter (KF), the highly accurate velocities provided by the DVL can be used to effectively restrain the error accumulation of the SINS [15; 16]. However, the dependency of the DVL signal on the acoustic environment may occasionally make the DVL malfunction [4]. Taking into account the work-mode against the seafloor in various seafloor environments, the DVL may malfunction in the following circumstances (shown in Figure 1):  
1. When the underwater vehicle sails across sea creatures, the acoustic wave emitted by the DVL cannot reach the seafloor. 2. When the strong wave-absorbing material (such as sludge) exists in the seafloor, the acoustic wave emitted by the DVL cannot be reflected back. 3. When the underwater vehicle sails over a trench, the distance between the vehicle and the bottom of the trench exceeds the measuring range of the DVL. 4. When the underwater vehicle performs large angle maneuvers, the DVL could malfunction under the condition of large roll and pitch. If the above-mentioned situations occur, it could lead to the loss of the DVL signal or the sudden changes of the velocity obtained from the DVL, and consequently the KF cannot get reliable external velocity information, which will cause the SINS errors to accumulate. As a result, the navigation system of the underwater vehicle cannot provide accurate navigation information anymore. So how to deal with DVL malfunctions for underwater integrated navigation systems is crucial. Over the past few decades, many solutions have been proposed to deal with sensor malfunctions in integrated navigation systems. The existing approaches can be classified into two broad categories: one is masking the faulty sensor or isolating the malfunction, and the other is finding a replacement for the faulty sensor or the KF. The first category is mostly implemented by two approaches: the use of hardware redundancy [17; 18], and the adjustment of navigation sensors utilization [19; 20; 21]. [PERSON] et al. [17] proposed a navigation system with two INS systems. By designing the hierarchical structure of the filters, each branch includes one of the INS sensors. Once one of INS sensors malfunctions, the system will shift to the other branch with the non-faulty INS sensor. This approach can deal with the malfunction for a long time but requires high hardware cost. To restrain the cost, approaches are developed based on filter technique to tune the utilization of sensor measurements.