Bio-inspired approach for long-range underwater navigation using model predictive control

Lots of evidence has indicated that many kinds of animals can achieve goal-oriented navigation by spatial cognition and dead reckoning. The geomagnetic field (GF) is a ubiquitous cue for navigation by these animals. Inspired by the goal-oriented navigation of animals, a novel long-distance underwater geomagnetic navigation (LDUGN) method is presented in this article, which only utilizes the declination component (D) and inclination component (I) of GF for underwater navigation without any prior knowledge of the geographical location or geomagnetic map. The D and I measured by high-precision geomagnetic sensors are compared periodically with that of the destination to determine the velocity and direction in the next step. A model predictive control (MPC) algorithm with control and state constraints is proposed to achieve the control and optimization of navigation trajectory. Because the optimal control is recalculated at each sampling instant, the MPC algorithm can overcome interferences of geomagnetic daily fluctuation, geomagnetic storms, ocean current, and geomagnetic local anomaly. The simulation results validate the feasibility and accuracy of the proposed algorithm

An Investigation into the Feasibility of Using a Modern Gravity Gradient Instrument for Passive Aircraft Navigation and Terrain Avoidance

Recently, Gravity Gradient Instruments (GGIs) - devices which measure the spatial derivatives of gravity, have improved remarkably due to development of accelerometer technologies. Specialized GGIs are currently flown on aircraft for geological purposes in the mining industries. As such, gravity gradient data is recorded in flight and detailed gradient maps are created after post mission processing. These maps, if stored in a database onboard an aircraft and combined with a GGI, form the basis for a covert navigation system using a map matching process. This system is completely passive and essentially unjammable. To determine feasibility of this method, a GGI sensor model was developed to investigate signal levels at representative flight conditions. Aircraft trajectories were simulated over modeled gravity gradient maps to determine the utility of flying modern GGIs in the roles of navigation and terrain avoidance. It was shown that the GGI based map-matching navigation system can likely provide a marked improvement over a non-aided INS but is limited by decreasing gravity gradient strength at higher altitudes, particularly over smooth terrain. Additionally, GGI output rate and bandwidth limitations, along with the inverse nature of the terrain avoidance problem, rendered GGI aided terrain avoidance unfeasible for the time being

Research on the Heat Dissipation Characteristics of Lithium Battery Spatial Layout in an AUV

To meet the power demand requirements of autonomous underwater vehicles (AUVs), the power supply is generally composed of a large number of high-energy lithium battery groups. The lithium battery heat dissipation properties not only affect the underwater vehicle performance but also bring some security risks. Based on the widespread application of lithium batteries, lithium batteries in an AUV are taken as an example to investigate the heat dissipation characteristics of the lithium battery spatial layout in an AUV. With the aim of increasing the safety of lithium batteries, a model is developed for the heat transfer process based on the energy conservation equation, and the battery heat dissipation characteristics of the spatial layout are analyzed. The results indicate that the most suitable distance between the cells and the cross arrangement is better than the sequence arrangement in terms of cooling characteristics. The temperature gradient and the temperature change inside the cabin with time are primarily affected by the navigation speed, but they have little relationship with the environmental temperature

Gravity Gradiometry and Map Matching: An Aid to Aircraft Inertial Navigation Systems

Inertial navigation systems (INS) offer passive, all-weather, and undeniable navigation information, which military customers often view as especially appealing strengths. Unfortunately, Airmen and engineers still struggle with INS’s drifting position errors, and navigation aids generally detract from INS’s strengths. At this year’s Air, Space, and Cyberspace in the 21st Century Conference, the Chief of Staff of the Air Force identified the Global Positioning System (GPS) as a widely-known and exploitable vulnerability, saying that it’s critical the Joint force reduce GPS dependence. Recent advances provide an opportunity for gravity gradient instruments (GGI), which measure spatial derivatives of the gravity vector, to aid an INS and preserve its strengths. This thesis shows that a GGI and map matching enhanced (GAME) INS improves navigation accuracy, presents the conditions that make GAME feasible for aircraft, and identifies opportunities for improvement. The methodology includes computer models and algorithms, where a GGI and map matching aid an INS through a Kalman filter. Simulations cover different terrains, altitudes, velocities, flight durations, INS drifts, update rates, components of the gravity gradient tensor, GGI and map noise levels, map resolutions, and levels of interpolation. Although GAME with today’s technology only appears worthwhile for long range and long endurance flights, the technologies expected in 10 years promise a broad spectrum of scenarios where GAME potentially provides great returns on investments and dominates the market for secure and covert navigation

Geomagnetic gradient-assisted evolutionary algorithm for long-range underwater navigation

Extensive research results have shown that animals like pigeons and turtles can use geomagnetic information for long-distance migration and homing. This article studies the bionic navigation method inspired by magnetotaxis behavior without prior knowledge. The problem of bionic geomagnetic navigation is generalized as an autonomous search of navigation path under the excitation of geomagnetic environment. The geomagnetic gradient-assisted evolutionary algorithm for long-range underwater navigation is proposed. In order to optimize the navigation path, the heading angle predicted by the geomagnetic gradient is used to constrain the sample space in the evolutionary algorithm. Then, according to the principle of multiparameter simultaneous convergence, the evaluation function is improved to enhance the reliability and accuracy of the navigation path. Simulations of the algorithm before and after improvement are carried out based on the data retrieved from the enhanced magnetic model (EMM). The performance of the improved method is evaluated and verified in the case of the area with normal geomagnetic field (GF), geomagnetic anomaly area, and multiple destinations. The simulation results show that the search efficiency and the straightness of the navigation path are greatly improved. The reason is that the constraint of sample space reduces the randomness in the process of navigation path search, and the improved evaluation function can evaluate the quality of samples more accurately. The improved algorithm also has good performance in the geomagnetic anomaly area, which indicates the potential application in the future

Internet of Underwater Things and Big Marine Data Analytics -- A Comprehensive Survey

The Internet of Underwater Things (IoUT) is an emerging communication ecosystem developed for connecting underwater objects in maritime and underwater environments. The IoUT technology is intricately linked with intelligent boats and ships, smart shores and oceans, automatic marine transportations, positioning and navigation, underwater exploration, disaster prediction and prevention, as well as with intelligent monitoring and security. The IoUT has an influence at various scales ranging from a small scientific observatory, to a midsized harbor, and to covering global oceanic trade. The network architecture of IoUT is intrinsically heterogeneous and should be sufficiently resilient to operate in harsh environments. This creates major challenges in terms of underwater communications, whilst relying on limited energy resources. Additionally, the volume, velocity, and variety of data produced by sensors, hydrophones, and cameras in IoUT is enormous, giving rise to the concept of Big Marine Data (BMD), which has its own processing challenges. Hence, conventional data processing techniques will falter, and bespoke Machine Learning (ML) solutions have to be employed for automatically learning the specific BMD behavior and features facilitating knowledge extraction and decision support. The motivation of this paper is to comprehensively survey the IoUT, BMD, and their synthesis. It also aims for exploring the nexus of BMD with ML. We set out from underwater data collection and then discuss the family of IoUT data communication techniques with an emphasis on the state-of-the-art research challenges. We then review the suite of ML solutions suitable for BMD handling and analytics. We treat the subject deductively from an educational perspective, critically appraising the material surveyed.Comment: 54 pages, 11 figures, 19 tables, IEEE Communications Surveys & Tutorials, peer-reviewed academic journa

Absolute Positioning Using the Earth\u27s Magnetic Anomaly Field

Achieving worldwide alternatives to GPS is a challenging engineering problem. Current GPS alternatives often suffer from limitations such as where and when the systems can operate. Navigation using the Earth\u27s magnetic anomaly field, which is globally available at all times, shows promise to overcome many of these limitations. We present a navigation filter which uses the Earth\u27s magnetic anomaly field as a navigation signal to aid an inertial navigation system (INS) in an aircraft. The filter utilizes highly-accurate optically pumped cesium (OPC) magnetometers to make scalar measurements of the Earth\u27s magnetic field and compare them to a map using a marginalized particle filter approach. We demonstrate navigation accuracy of 13 meters DRMS with a high quality magnetic anomaly map at low altitudes with real flight data. We conduct a simulation over the continental United States to predict accuracies with respect to variables like location and altitude. Finally, we address the problem of map availability by presenting a method for a self-building magnetic anomaly model

Autonomous Vehicles

This edited volume, Autonomous Vehicles, is a collection of reviewed and relevant research chapters, offering a comprehensive overview of recent developments in the field of vehicle autonomy. The book comprises nine chapters authored by various researchers and edited by an expert active in the field of study. All chapters are complete in itself but united under a common research study topic. This publication aims to provide a thorough overview of the latest research efforts by international authors, open new possible research paths for further novel developments, and to inspire the younger generations into pursuing relevant academic studies and professional careers within the autonomous vehicle field

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties