自然水体中超声波标记鱼游动轨迹精密确定算法

针对鱼类关键生境位置确定的应用需求,该文提出了一套适用于自然水体的超声波标记鱼定位算法,解决了标记鱼定位以及存在粗差观测值,即水听器记录的超声波信号接收时间存在错误情况下算法的抗干扰性。宜昌黄柏河的实测结果表明,基于现有1 ms级精度的水听器,可在自然水体中获得2.15 m精度的信号标记鱼三维游动轨迹。如因气泡、遮挡等因素对水听器观测数据引入粗差,当粗差量级在10 m以上,该方法可接近100%探测出是否存在粗差。当粗差观测值在3个以内时,该方法的探测成功率可达84.3%以上,3个以上时粗差探测成功率明显下降,5个及以上,即粗差观测值个数占观测值总数的比例大于31.25%时,基本只能探测出观测数据中存在粗差而无法有效确定粗差。该研究可为渔业增殖、鱼类栖息地保护、鱼类洄游通道等研究提供参考。

Accurate determination algorithm of swimming trajectory for ultrasonically-tagged fish in natural water

Abstract: An important goal of hydrobiology is the simulation, reconstruction and restoration of important fish habitats, in which fish species form aquatic ecosystems'' climax communities, enabling structural and functional restoration of river ecosystems. Traditional methods for identifying key fish habitat locations such as spawning grounds, include fish resource surveys, observation of fish spawning behavior and interviews with fishermen. But these are subject to problems including poor accuracy and large error. Precise positioning of fish can accurately locate key habitats (such as spawning grounds) based on key life cycle phases (such as spawning periods), permitting observation of corresponding habitat parameters. Fish movement trajectory data can also deepen understanding of fish habits and habitats, permitting suitable habitat indicators to be scientifically determined, and providing theoretical and technical support for fish protection and habitat restoration efforts. Ultrasonic tag tracking technology is widely used in fish behavior research due to its long underwater propagation distance and broad applicability. But most existing researches derived fish movement trajectories from hydrophone data using equipment manufacturers'' software or services, and few articles concerning fish positioning principles and methods optimized for natural aquatic environments have been published. The Chan''s algorithm (1994) in literature[24] and robust least squares estimation were combined to get the location of ultrasonically-tagged fish in this paper, leveraging the strengths of these methods to overcome their disadvantages when used singly. Chan''s algorithm was first used to obtain approximate coordinates of fish, which were used as initial position estimates from which the final position estimates were obtained with robust least squares. Prior information such as water depth and fish swimming speed could also be taken into account, making the proposed positioning method well-suited for dealing with ultrasonically-tagged fish in natural aquatic environments. The proposed method was suitable for existing ultrasound hydrophones, and effectively solved problems with large observation errors. Based on these research results, the UWP (under water positioning) software package was developed. To verify the effectiveness of the proposed method, an observation network was constructed which consisting of 16 hydrophones uniformly distributed over a area of 120 m×120 m in Huangbai River, Yichang. 4 ultrasonic signal tags were used to evaluate the positioning results, 2 was co-located with hydrophones for static simulation, and the other 2 affixed to a boat hull for dynamic simulation. Comparisons with Beidou/GNSS RTK with centimeter-level accuracy positioning estimates over 115 groups of test results, using millisecond-level accuracy observation data from existing hydrophones, swimming trajectories of ultrasonically-tagged fish could be obtained to an accuracy of about 2.15 m. While complex water environments degraded this accuracy, where single observations contained gross errors exceeding 10 m, 100% of these errors could be identified. The success rate for identification of observations with gross error was a gradually declining function of gross errors, dropping to 84.3% for 3 such observations. With over 3 gross error-bearing observations, the success rate declined significantly. With over 5 gross error-bearing observations where gross error-bearing observations accounted for over 31.25% of all observations, application of the proposed method could detect the error'' existence, but was unable to identify the error-bearing observations effectively. The ultrasonic tag precise positioning method of fish proposed in this paper provide an effective method for determining the accurate swimming trajectory of fish in rivers, lakes and seas with low visibility. In addition, by modifying the data communication interface, this method can be effectively applied to ultrasonicall-taggeds fish and hydrophones of different manufacturers. In the future, it can play a more important role in promoting ecological environmental protection, and human beings'' understanding of ecological and behavioral evolution in the aquatic environment at the population level.