Water quality sampling and monitoring unmanned boat plays an important role in water environment monitoring, and navigation and positioning accuracy is the key to ensure that it can accurately reach the sampling point and obtain effective data. Complex water environment such as strong current, multiple obstacles, signal blocking, etc. will interfere with the navigation and positioning accuracy of water quality sampling and monitoring unmanned boat, so a series of measures need to be taken to deal with these challenges.
Complex water environment will bring various interferences to the navigation and positioning of water quality sampling and monitoring unmanned boat. For example, strong water currents will cause the water quality sampling and monitoring unmanned boat to deviate from the scheduled route, resulting in increased positioning errors. Obstacles in the water such as reefs and sunken ships may affect the navigation safety of water quality sampling and monitoring unmanned boats, and will also interfere with signal propagation and affect positioning accuracy. In addition, in some narrow rivers or waters surrounded by tall buildings, satellite signals may be blocked, making the satellite positioning-based system unable to work properly.
In order to cope with the interference of complex water environment, water quality sampling and monitoring unmanned boats usually adopt a fusion of multiple positioning technologies. Common ones are the fusion of global satellite navigation system (GNSS) and inertial navigation system (INS). GNSS can provide high-precision absolute position information, but it will fail when the signal is blocked; INS estimates the position by measuring acceleration and angular velocity, which is not affected by external signals, but the error will accumulate over time. After the two are integrated, when the satellite signal is good, GNSS provides calibration for INS to improve positioning accuracy; when the satellite signal is blocked, INS continues to work to maintain navigation and positioning functions, ensuring that the water quality sampling and monitoring unmanned boat can continue to sail accurately.
The water quality sampling and monitoring unmanned boat can also use environmental perception technology to assist in positioning. For example, installing a sonar system to detect underwater terrain and obstacles by transmitting and receiving sound waves can not only be used for obstacle avoidance, but also for positioning in combination with electronic charts. When the satellite signal is limited, the terrain information obtained by the sonar can be matched with the pre-stored map data to determine the location of the water quality sampling and monitoring unmanned boat. In addition, visual sensors can also be used to identify surface markers or shore features, and assist positioning through image analysis to further improve the accuracy and reliability of navigation positioning.
In view of the influence of water flow on navigation and positioning accuracy, the water quality sampling and monitoring unmanned boat will be equipped with water flow sensors to monitor the speed and direction of water flow in real time. By obtaining water flow information, combined with the navigation speed and attitude data of the water quality sampling and monitoring unmanned boat, the positioning result is compensated in real time using algorithms. In this way, even in a strong water flow environment, the water quality sampling and monitoring unmanned boat can adjust the route in time according to the influence of the water flow, keep operating near the predetermined sampling point, and effectively improve the navigation and positioning accuracy.
Advanced navigation algorithms are the key to improving the navigation and positioning accuracy of water quality sampling and monitoring unmanned boats. By establishing a mathematical model of complex water environments, various interference factors are taken into consideration and adaptive navigation algorithms are designed. These algorithms can dynamically adjust the navigation strategy of the water quality sampling and monitoring unmanned boat according to the real-time environmental information and sensor data, optimize the route planning, and enable the water quality sampling and monitoring unmanned boat to navigate on the optimal path when facing different complex water environments, reduce positioning errors, and improve the accuracy and stability of navigation and positioning.
The water quality sampling and monitoring unmanned boat effectively copes with the interference of complex water environment on navigation and positioning accuracy through the integration of multiple positioning technologies, environmental perception technology assistance, real-time water flow monitoring compensation, and optimization of navigation algorithms. The comprehensive application of these measures enables the water quality sampling and monitoring unmanned boat to accurately navigate in various complex water conditions and reach the predetermined sampling points, providing reliable data support for water quality monitoring, thereby better serving the monitoring and protection of the water environment.
