Passive Target Tracking in Underwater Environment using Bearing and Frequency Measurements

The tracking of underwater targets represents a basic unit in underwater surveillance for offering effective search and rescue operations. However, the tracking of the target is a major constraint in finding the underwater target. This paper devises a model for underwater target tracking considering radar signals. Radar signals are subjected to the image reconstruction process to make them suitable for further processing. The gridding is the next step, which is utilized for generating the grids to focus on each region in a precise manner. The features like Ridgelet transform and Local Gabor XOR Pattern (LGXP) are produced. Data augmentation is the next process, which helps to reduce the size of data by performing resizing. At last, the tracking of targets is performed from each grid with a Deep neuro fuzzy network (DNFN). Here, DNFN training is performed with Exponential-Competitive Swarm Optimization (E-CSO), which is derived by integrating Exponential Weighted Moving Average (EWMA) and Competitive Swarm Optimization (CSO). The proposed E-CSO-based DNFN offered high efficiency with a maximal detection rate of 98.8%, minimal Mean square error of 0.012, and Mean Absolute Percentage Error (MAPE) of 17.883.

A major advantage of the use of passive sonar in the tracking multiple underwater targets is that they can be kept covert, which reduces the risk of being attacked. However, the nonlinearity of the passive Doppler and bearing measurements, the range unobservability problem, and the complexity of data association between measurements and targets make the problem of underwater passive multiple target tracking challenging. To deal with these problems, the cardinalized probability hypothesis density (CPHD) recursion, which is based on Bayesian information theory, is developed to handle the data association uncertainty, and to acquire existing targets’ numbers and states (e.g., position and velocity). The key idea of the CPHD recursion is to simultaneously estimate the targets’ intensity and the probability distribution of the number of targets. The CPHD recursion is the first moment approximation of the Bayesian multiple targets filter, which avoids the data association procedure between the targets and measurements including clutter. The Bayesian-filter-based extended Kalman filter (EKF) is applied to deal with the nonlinear bearing and Doppler measurements. The experimental results show that the EKF-based CPHD recursion works well in the underwater passive multiple target tracking system in cluttered and noisy environments.

Coastal and marine resource use conflicts and sustainable development in Tanzania

The object of research of this article is interstate relations in the field of legal regulation of the use of marine genetic resources. The author presents a detailed analysis of the concept of "marine genetic resources", draws a distinction with other similar concepts used in international legal acts. The current international legal acts in this area are considered in detail, as well as the draft of an International legally binding Document on the conservation and sustainable use of marine biological diversity in areas beyond the limits of national jurisdiction. A number of problems related to the international legal regulation of the use of marine genetic resources are identified. Comparative legal analysis, formal legal, formal logical and system methods, methods of analysis and generalization were used as the main methodology of the study. The novelty of this study lies in the fact that at the moment there is no universal international legal act that would regulate the use of marine genetic resources. It is also necessary to note a small number of scientific papers, mainly by foreign authors, devoted to this topic. At the same time, such resources have found wide application in various branches of science and production. Taking into account the above, it seems relevant to conduct additional scientific research aimed at studying the international legal regime of marine genetic resources. As a result of the presented research, the analysis of the concepts of "marine genetic resources", "genetic material", "marine biological resources", "living marine resources" was carried out. A number of problems in the international legal regulation of this sphere have been identified. So, in particular, the extension of the principle of the common heritage of mankind to marine genetic resources, if it is impossible to extend this principle to the open sea, may further generate legal conflicts. The author comes to the conclusion that it is necessary to further study the international legal regime of marine genetic resources.

The level of biodiversity in Indonesia as a tropical country is very high, the potential of marine biological resource makes the sea of Indonesia called as Marine Mega-Biodiversity region in the world. Therefore it was expected especially in coastal communities can take and utilizing of marine biological resource optimally, especially for conventional and traditional for health. However basical knowledge and attitude of coastal communities about coastal and marine resources primarily for its management is still lack. The lack of the basical knowledge can affect the inability of society to engage in the use of coastal and marine resources, especially the utilization of marine biological resources in health. The aim of this research was to determine the relationship between knowledge and attitude to the utilization of marine biological resource for health on coastal communities area of Soropia wich one of coastal areas in Southeast Sulawesi with high potential of marine biological resorces. The research method used observational design with cross sectional approach. The subjects of the research were coastal communities in Soropia located in three villages, namely Tapulaga, Leppe and Bajoe. This research was conducted for January 2016, with 292 respondents of population. The sample were selected by using stratified random sampling technique that obtained 167 respondents. Bivariate analysis was performed by Chi square and Fisher test.The result of bivariate analysis showed that there was significant relationship between knowledge (p=0,000) and the utilization of marine biological resource for health and there was significant relationship between attitude (p=0,014) and the utilization of marine biological resource for health. This research concluded that there were significant relationship between knowledge and attitude to the utilization of marine biological resource for health in the coastal community area of Soropia. The present research suggested that there would be further research that investigated the efficacy of Enhalus acoroides root as the alternative treatment to resolve Diabetes disease, Semele cordiformis as the alternative medication to cure Hepatitis disease and Siganus sp. bile as the alternative analgesic medication to wounds caused by fish bone. Keywords: marine biological resource,health, knowledge, attitude, coastal community

Using traditional sonar arrays may be difficult and impractical in some mission-critical scenarios, because they should be mounted on or towed by a ship or a submersible. Alternatively, underwater acoustic sensor networks (UW-ASNs) offer a promising solution approach. In this paper, a target-tracking algorithm for UW-ASNs, i.e., 3-D underwater target tracking (3DUT), is presented. The objective of 3DUT is to collaboratively accomplish accurate tracking of underwater targets with minimum energy expenditure. Based on the time of arrival of the echoes from the target after transmitting acoustic pulses from the sensors, the ranges of the nodes to the target are determined, and trilateration is used to obtain the location of the target. The location and the calculated velocity of the target are then exploited to achieve tracking. To realize energy-effective target tracking, 3DUT incorporates a new target-movement-based duty-cycle mechanism. To avoid rapid depletion of the energy resources of boundary nodes due to continuous surveillance, 3DUT employs an adaptive procedure to find, designate, and activate new boundary nodes. Performance evaluation shows that 3DUT is a promising alternative to the traditional sonar-based target-tracking approaches, particularly for on-demand surveillance applications.

In this paper, according to the characteristics of underwater target tracking, extended Kalman filter (EKF) algorithm was applied to address underwater bearing-only non-maneuverable target tracking problem. To ensure the observability in bearing-only passive target tracking, we use two sensor arrays in uniform rectilinear motion to track the single target. EKF is recursive Bayesian filter algorithm based on the linearization of the nonlinearities in the state and the measurement system. And the simulation experiment shows that, to the constant velocity single target, the bearings-only EKF algorithm with dual-array has good results, also the EKF has lower computation complexity than unscented Kalman filter and particle filter. It confirms the effectiveness of the EKF algorithm in solving the underwater bearing-only target tracking problem.

The underwater target tracking environment usually has the characteristics of strong nonlinearity and non-Gaussian. The target tracking problem usually uses the nonlinear filtering algorithm, which combines the nonlinear measurement model with the linear system dynamics. The primary goal of target tracking is to extract accurate information about the real-time state of the target from the noise nonlinear observation obtained by the sensor. A new Gaussian Hermitt Kalman particle filter algorithm (GHKF-PF) is used to improve the tracking accuracy of the particle filter algorithm (PF). GHKF-PF uses the GHKF sampling method to sample particles from the posterior distribution of the target, calculates the mean and covariance for each particle, and uses the mean and variance to guide sampling. In the simulation experiment, the uniform linear motion model of underwater 3D target in the environment of Gaussian mixture noise (GMN) is established, and the application of GHKF-PF algorithm in 3D space is realized, and the accuracy is higher than that of PF. In order to further verify the effectiveness of the algorithm, a six-dimensional uniform acceleration motion model is established and compared with the extended particle filter (EPF) algorithm and the unscented particle filter (UPF) algorithm. The simulation results show that the performance of the GHKF-PF algorithm is similar to that of the UPF algorithm and better than the EPF algorithm.

The underwater sensor network is currently a hot research field in academia and industry with many underwater applications, such as ocean monitoring, seismic monitoring, environment monitoring, and seabed exploration. Underwater target tracking is a critical component of ocean development. This paper studies the underwater target tracking problem of the wireless sensor network. The core technology of the target tracking algorithm is the filtering algorithm, which identifies the accuracy of the target tracking system. Nonlinear filtering is a hot issue in target tracking because feasible projects are mostly non-linear systems. The linearization method used in traditional Kalman filtering has serious shortcomings. Therefore, this paper presents the improved cubature Kalman filtering (ICKF) algorithm for underwater target tracking. There is uncertainty in the target movement, an adaptive forgetting factor is given into the cubature Kalman filtering algorithm to directly modify the error covariance to reduce the impact of uncertainties. Then, interactive multi-model technology is introduced to establish the IMMICKF algorithm with multiple states. Compared with other filtering algorithms, the new algorithm can effectively deal with non-linear target tracking problems and obtain better estimation accuracy. The numerical simulation is given to demonstrate the effectiveness of the IMMICKF algorithm.

A new approach to the optimal formation problem is proposed in the sense of the passive target tracking using time difference of arrival (TDOA) data obtained by cooperative UAVs. In most existing methods, under the assumption that arbitrary unbiased and efficient estimator could be designed for target tracking, the objective function for the information maximizing formation is defined without particular consideration of the filter structure used for passive target tracking. However, this approach might be restrictive because the overall performance of passive target tracking depend on the UAV formation and the filter structure as well. To overcome this limitation, the proposed technique takes account of the practical tracking filter structure and its properties in the problem. To do this, it is firstly shown that the amount of moving target information is expressed in terms of the variance of UAVs' angular positions. In order to guarantee the satisfactory target tracking performance even when the UAVs-target relative geometry is time-varying, the optimal formation problem is formulated as finding the maximizing solution of the objective function in worst-case. Through the simulations, the effectiveness of the proposed scheme is demonstrated.

In this work, we develop shifted Rayleigh filter (SRF) for continuous-discrete (CD) systems. The proposed filter is applied to a real-life underwater passive bearings-only target tracking problem, where the discretization error is accounted for. The stochastic differential equation describing the process dynamics is approximated using Ito-Taylor expansion of order 1.5. Inorder to make a fair comparative study, the performance of the proposed algorithm, which we refer to as CD-SRF, is examined with other popular filters like the unscented Kalman filter (UKF), cubature Kalman filter (CKF) and Gauss-Hermite filter (GHF) in the CD domain. The filtering performance has been studied in terms of root mean square error (RMSE), track-loss and computational time. Theoretical Cramer-Rao lower bound (CRLB) is also implemented to determine the maximum achievable accuracy.

Underwater target tracking system can be kept covert using the bearing-only or the bearing-Doppler measurements (passive measurements), which will reduce the risk of been detected. According to the characteristics of underwater target tracking, the square root unscented Kalman filter (SRUKF) algorithm, which is based on the Bayesian theory, was applied to the underwater bearing-only and bearing-Doppler non-maneuverable target tracking problem. Aiming at the shortcomings of the unscented Kalman filter (UKF), the SRUKF uses the QR decomposition and the Cholesky factor updating, in order to avoid that the process noise covariance matrix loses its positive definiteness during the target tracking period. The SRUKF uses sigma sampling to avoid the linearization of the nonlinear bearing-only and the bearing-Doppler measurements. To ensure the target state observability in underwater target tracking, the paper uses single maneuvering observer to track the single non-maneuverable target. The simulation results show that the SRUKF has better tracking performance than the extended Kalman filter (EKF) and the UKF in tracking accuracy and stability, and the computational complexity of the SRUKF algorithm is low.

Conventional passive tracking methods for underwater acoustic targets in sonar engineering generate time azimuth histogram and use it as a basis for target azimuth and tracking. Passive underwater acoustic targets only have azimuth information on the time azimuth histogram, which is easy to be lost and disturbed by ocean noise. To improve the accuracy of passive tracking, we propose to adopt the processed multi-beam Low Frequency Analysis and Recording (LOFAR) as the dataset for passive tracking. In this paper, an improved LeNet-5 convolutional neural network model (CNN) model is used to identify targets, and a passive tracking method for underwater acoustic targets based on multi-beam LOFAR and deep learning is proposed, combined with Extended Kalman Filter (EKF) to improve the tracking accuracy. The performance of the method under realistic conditions is evaluated through simulation analysis and validation using data obtained from marine experiments.

PDF HTML阅读 XML下载 导出引用 引用提醒 海洋可持续发展目标与海洋和滨海生态系统管理 DOI: 10.5846/stxb201702040211 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金重点国际合作项目（41420104004）；科技基础性工作专项（2013FY111100）；UNEP项目（DTIE16-SC057） Sustainable Development Goals for oceans and marine and coastal ecosystem-based management Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:海洋和海岸带可以为人类提供多种生态系统服务，保护与持续利用海洋资源以促进海洋和海岸带可持续发展已被正式纳入联合国可持续发展目标。实施海洋可持续发展目标面临几大挑战，包括如何减小陆基人类活动的影响、加强海岸带的综合管理、提高海洋资源效率、适应气候变化和提高沿海居民的人类福祉等。为应对这些挑战，需要将海洋和海岸带融合为一个大型生态系统，利用基于生态系统的管理方法，综合考虑各个部门和多种胁迫因素的累积影响，通过建立综合的海洋观测体系，合理划分海洋功能区，按照海洋环境承载力限制陆基人类活动，合理配置并有效利用海洋资源，提升海洋和海岸带生态系统的整体服务功能，从而进一步推进实施海洋可持续发展目标。 Abstract:Ocean and coast can provide a variety of ecosystem services. "Conserve and sustainably use the oceans, seas and marine resources" has been addressed in the United Nations Sustainable Development Goals (SDGs). Challenges for the implementation of marine SDGs include how to reduce the impacts of land-based activities, strengthen integrated coastal management, improve marine resource efficiency, enhance climate change adaptation, and thus improve human well-being for coastal zone residents. To address these challenges, ocean and coasts should be integrated as a whole ecosystem and marine and coastal ecosystem-based management should be applied to take into account the cumulative impacts from multi-sectors and different stressors. Ecosystem services provided by ocean and coasts can be improved by setting up integrated marine observation system, performing reasonable marine zoning, reducing human activities based on the carrying capacity of marine environment, and ensuring reasonable allocation and use of marine resources. All these measures can move forward the implementation of marine Sustainable Development Goals (SDGs). 参考文献 相似文献 引证文献

Observability analysis of two closed-loop guidance systems with bearings-only measurements