面向渔业物联网的 GPS 相对定位策略.

Modern fishery farming is developing in the direction of refinement, and the application of the Internet of Things in fisheries is becoming more and more widely used. For the deployed terminal nodes, in addition to the need to obtain environmental awareness information, it is also necessary to obtain the location information of the node, so that the collected data have application value. Moreover, the higher the positioning accuracy of the node, the better the evaluation of the environmental state and the task execution, especially for the node with a buoy as the carrier. At present, the positioning accuracy of Global Positioning System (GPS) technology widely used is about 10 m, the use of RTK differential technology obtain high positioning accuracy, but the equipment price is too high, so it is not very suitable for fishery application. In this study, a low-cost GPS relative positioning method based on the Long Range (LoRa) network was proposed. First, the relative positioning strategy data model was established through error analysis, and then the relative positioning method based on the LoRa network and improved the Time Division Multiple Access (TDMA) transmission strategies were designed to achieve high-precision positioning and energy-efficient data transmission. The premise of the relative positioning of this study was that time synchronization could be achieved, GPS receiver provided accurate timing service, so before nodes started to locate, all nodes in the network were synchronized through GPS module, and every fixed cycle of synchronization operations, to ensure that all nodes had the same time benchmark. Gateways and terminals caused similar system errors due to atmospheric delay, convection, and ionosphere effects, and improved relative position accuracy through relative positioning calculation. The transmission of data based on the LoRa network was fully taken into account that LoRa was suitable for long-distance transmission, which was sufficient for applications in large fisheries environments. Secondly, the low power consumption of LoRa also reduced the cost of fishery production. When the terminal carried out information collection, LoRa went into a dormant state after the completion of work, which effectively reduced the power consumption. In this study, the latitude and longitude information of the gateway and terminal was set up to consist of an observation sequence consisting of satellite signal strength greater than 30 dB in the observed satellite, and each positioning required that the gateway and the terminal had more than 6 same satellites. Considering a large number of nodes in the Internet of Things system, to prevent information collision affected the positioning accuracy, the introduced TDMA technology assigned each terminal its time slot. Each terminal starts its work according to its task and then uploaded data. The transmission strategy of this study was different from the previous strategy, which stipulated that each cycle should firstly collect or locate the data according to the task broadcast in the previous cycle, then broadcasted the task of the next cycle, and finally the terminal response. This shortened the cycle and increased the reliability of information transmission. Finally, the hardware node was designed and the deployment test was carried out in the offshore fishery. The test calculation took the gateway as the origin, the positive east direction was the x-axis, the north direction is the Y-axis to establish a coordinate system, Vincenty method using the ellipsoid model to ensure the accuracy of the calculation. The experimental data showed the validity and reliability of the proposed method in this study. With a low-cost GPS commercial module, the average positioning accuracy of the terminal nodes 1 000 and 499 m from the gateway increased from 10 m to 4.8 and 2.4 m, respectively, and the data delivery rate increased from 80% to more than 95% [ABSTRACT FROM AUTHOR]