水库大坝时刻面临裂缝或渗漏等影响安全运行的不确定因素，确定表面缺陷位置对病坝老库的加固至关重要。本项目应用短基线和捷联惯导协同效应，构建用于库坝ROV表面缺陷定位的异构网络，针对库坝特殊结构下ROV定位存在非高斯噪声、水声丢包以及悬停增强等问题，开展不稳定异构网络非高斯噪声下库坝ROV时空耦合增强定位研究。重点开展：（1）提出水声基阵优化部署联合坝面垂向约束的短基线定位解算方法，融合偏航约束和误差链传播特性研究捷联惯导位姿更新算法；（2）考虑异构网络非高斯噪声及水声信号丢包建立库坝ROV耦合定位模型，提出异构网络定位输出不稳定乃至失效的自修复方法；（3）识别并剔除非线性耦合定位输出的异常值，提出库坝ROV悬停时局部典型时空关联的增强定位。通过搭建基于异构网络的库坝ROV定位平台来开展综合实验验证。研究成果可为库坝ROV缺陷定位提供理论支持，对重大库坝的实时监控和防灾减灾具有实际意义。

Reservoir dams face the uncertain factors every moment such as cracks or leakages that affect the safe operation. It is of great significance to determine the surface defect position of the old reservoir dams for the defect reinforcement. To address the non-Gaussian noises, acoustic packet loss and hover enhancement in reservoir dam special structure, this project applies the cooperative effect of short baseline and strapdown inertial navigation system to construct heterogeneous networks for ROV positioning in reservoir dam. This project carries out the research of the spatiotemporal coupling enhancement positioning for reservoir dam ROV under non-Gaussian noises of unstable heterogeneous networks. This project will focus on addressing three contents. (1) ROV underwater short baseline positioning method is proposed based on the combination of the acoustic array optimal deployment and dam surface vertical constraint, while ROV position and attitude updating algorithm is established under the yaw constraint and the error chain propagation characteristics. (2) ROV coupling positioning model is built in consideration of non-Gaussian noises and underwater acoustic signal loss, while ROV positioning self-repairing method is proposed under the unstable and failure of heterogeneous networks. (3) The outliers of ROV nonlinear coupling position outputs are recognized and eliminated, while ROV enhanced positioning algorithm is proposed under local typical spatiotemporal correlation. An experimental platform of position detection for reservoir dam ROV is constructed based on heterogeneous networks. Then a comprehensive performance test is conducted to evaluate ROV positioning performance. The research results can provide theoretical support for ROV defect positioning in reservoir dams, and have practical significance for real-time monitoring, disaster prevention and mitigation of major reservoir dams.