Position Fixing Research Articles

Depth-based vessel position fixing by means of a neural network

A depth-based vessel position fixing method on the basis of a neural network is proposed. The network takes as an input a sequence of depth values measured by an echo-sounder and predicts vessel latitude and longitude for the moment of the latest depth measurement. The neural network has a fully-connected feedforward architecture with several layers which satisfies conditions of the universal approximation in compliance with the Stone-Weierstrass theorem. The Adamax algorithm for the neural network training with controlling a maximum value of position error at each epoch is implemented. Modeling is conducted with the Python programming language and the Tensorflow library. The model surface of seabed is performed as a second-order polynomial. Training samples on the basis of virtual soundings at the coordinate net knots with the space resolution not worse than one cable are obtained. After samples obtaining the training of the neural network is conducted. A validation set is not used. Several neural networks are trained. They have different number of hidden layers and different number of neurons per each hidden layer. After training the test procedure is performed. Test samples are generated in the assumption that a vessel is moving along meridians which are not used at the stage of the preliminary soundings survey. The cases of mean and random test meridians are considered. The random meridians are obtained with a uniform random number generator. As the result, all the tested neural networks have shown approximately identical navigational accuracy which is close to the accuracy for the training set.

Wideband millimeter-wave reflectarray antenna with reduced cross-polarization

Abstract A novel wideband reflectarray antenna (RA) is designed for 5G millimeter (mm) wave communications in the frequency range of 26.5–36 GHz. The proposed unit cell is constructed using a grid periodicity of 0.52 ${{\lambda }_0}{ }$ that offers 636° phase change through phase delay lines (PDLs) ( ${{\theta }_{\text{s}}}$ ). These PDLs are attached to the outer end of the unit cell comprising semi-circular rings. Bandwidth enhancement is achieved by incorporating a corrugated slot technique and a suitable air gap beneath the substrate. The proposed center-fed reflectarray is composed of 513 elements distributed in a circular aperture (13.46 ${{\lambda }_0}$ ). Using mirror-symmetrical distribution of the unit cells, a cross-polarization reduction as low as −50 dB is realized. At 30 GHz, RA has a measured peak gain of 28.2 dBi, a sidelobe level of −14.3 dB, and an aperture efficiency of 31.4%. The prototype antenna is fabricated, and the simulation results are experimentally validated. The measured 1-dB and 3-dB gain bandwidths of the proposed reflectarray antenna are 31.3% and 41.6%, respectively. The proposed broadband reflectarray can be a potential choice for inter-satellite services like inter-satellite networking/satellite positioning and control; fixed satellite services such as GPS satellite synchronization and data direct to home TV; and satellite position fixing.

Celestial Navigation as the Emergency GNSS Backup: Enhancing Navigational Reliability

The development of Global Navigational Satellite Systems (GNSS) has revolutionised navigation on ships. GNSS, together with electronic chart display information system (ECDIS), has made navigation more accurate, efficient, and safer for sailors. However GNSS signals can be affected by various factors such as spoofing, jamming, ionospheric disturbances etc., while no backup means of position fixing in the open sea are available on board ships. Over-reliance on GNSS without the development of an alternative backup will jeopardise safe navigation of ships. However, most of the alternatives available are either complicated or expensive. By changing certain regulations and further development celestial navigation, a reliable and cost-effective backup system can be obtained.

Snapshot GNSS receivers for low-effort, high-gain space situational awareness

This paper proposes a novel concept of using highly efficient Snapshot Global Navigation Satellite Systems (GNSS) receivers to provide precise position fixes of single or multiple satellites in Low-Earth Orbit (LEO) to improve upper atmospheric modeling and thus contribute to superior space situational awareness (SSA). While tracking of LEO satellites and the use of onboard GNSS receivers for drag measurements and upper atmosphere modeling are well-established techniques, the expected advent of snapshot GNSS receivers for spaceborne scientific applications will allow massive improvements on the GNSS sensor’s Size, Weight, Power and Cost (SWaP-C). With chip-size dimensions of 4x4 mm2, a mass of less than 5 gr, an average power level below 0.1 mW, snapshot receiver technology is expected to provide position fixes in space with an accuracy of ∼19 m (3D r.m.s.), which will surpass the accuracy of Two-Line Elements (TLE) provided by the US Joint Space Operations Center (JSpOC) by at least two orders of magnitude. Equally important to their SWaP-C benefits, Snapshot GNSS receivers will allow mission and spacecraft designers to trade onboard-processing requirements versus payload downlink requirements, leading to either minimum onboard processing or a minimum amount of downlinked data. In this research, we establish the concept and architectural overview of using snapshot GNSS receivers for SSA, including the role of using them in a Distributed Space System (DSS), and detail their characterization and performance in terms of the required GNSS hardware and the impact of these payload on the power budget, the link budget and the OnBoard Data Handling (OBDH) budget of a satellite. It will be shown that these receivers lend themselves especially to their use on femto-, pico- and nano-satellites, although integrated snapshot modules may be flown as auxiliary payloads on micro- or mini-satellites as well. While this work focuses on the implications of the use of snapshot GNSS receivers on spacecraft design for the use of upper atmosphere modeling and SSA, their use may open up other science applications which avoid the need for expensive high-grade GNSS receivers.

Neural network-based method for determining vessel position by seabed relief

A seabed relief-based vessel position fixing model on the basis of a four-layered feedforward neural network is proposed. Hidden neurons have hyperbolic tangent activation functions. The model is constructed for 1-D case that can be considered as vessel motion throw a narrow channel or alongside fairway axis. A sequence of spot soundings is given for the network input. The linear coordinate registered for the last sounding forms the network output. The training set is formed by means of the intentional pseudorandom alteration of input samples in accordance with suspected limits of sea level variations and the constant error of its measurements. The validation set is not used. The Adamax algorithm is implemented for the neural network training. The maximum of absolute value of the prediction error is used as a performance criterion of the net. Modeling has been conducted with the Python programming language. The Tensorflow library is used for the creation, training and testing of the neural network. The depth is modelled as a piecewise polynomial function of the coordinate. The results of neural network testing with the use of noised input samples let to state that the neural net can determine a ship position by means of soundings with acceptable accuracy. Different combinations of the sea level error and the number of hidden neurons have been considered. For each of such combinations the network accuracy indicators have been calculated. The best results are obtained for the network with 100 hidden neurons per each layer.

Azimuthal, range, and depth tracking of marine mammal sounds using a drifting acoustic vector sensor and hydrophone array platform

Deep-water acoustic tracking of marine mammals typically requires correlating hydrophone signals across both short and large-aperture hydrophone arrays. Here, we demonstrate how a single drifting, depth-controlled platform can obtain two and three-dimensional positional fixes of marine mammal sounds using an acoustic vector sensor and short-aperture arrays, both mounted on an autonomous drifting platform. In February and June 2023 two autonomous opto-acoustic drifters were deployed 50km off San Diego, CA at 250 m depth in 1030 m deep water. Both drifters were equipped with a CTD and acoustic recording system comprised of a 1.75 m aperture vertical hydrophone array, a tetrahedral hydrophone array, and either a 2-D Geospectrum M-35 or 3-D Wilcoxon VS-209 acoustic vector sensor. Throughout the two to three-day deployments, all acoustic sensors detected numerous marine mammal calls, including humpback whales and a pod of common dolphins. Estimates of azimuth and elevation were obtained from the simultaneously sampled acoustic vector sensor and hydrophone arrays, while multi-path and cross-platform processing were employed to extract range information. The results suggest that sparse deployments of drifting vector sensor platforms may be able to map biological distributions over spatial scales that would otherwise require larger numbers of hydrophone-only platforms. [Work supported by ONR TFO.]

Seabed relief-based vessel position fixing with a neural network

A seabed relief-based vessel position fixing system on the basis of a neural network is proposed. The neural network satisfies the conditions of the universal approximation theorem and has one hidden layer. The hidden neurons have hyperbolic tangent activation functions. The model is constructed for 1-D case that can be considered as vessel motion throw a narrow channel or fairway. A sequence of depth derivatives (in relation to the coordinate) is fed to the network input. The depth is assumed to be measured with an echo-sounder. The vessel linear coordinate registered for the last depth derivative is formed on the network output. The training set contains not only data presumably registered at the stage of preliminary depth survey but also their noise-added versions obtained with the use of a random number generator. The validation set contains the survey data only. The Adamax algorithm is implemented for the neural network training. The maximum of absolute value of the prediction error is used as a performance criterion of the net. Modeling has been conducted in Python with Tensorflow. The depth is considered to be a polynomial function of the coordinate at each path region. So, the depth derivatives can be calculated analytically. As the result it is possible to state that the neural network predicts a vessel position with acceptable accuracy even in input signal noise conditions. Moreover, the neural network architecture of the radial-basis functions has been examined, but it is not possible to achieve acceptable accuracy by using it. The conducted investigations of the influences of a mini-batch size and learning rate values on the accuracy has shown that these parameters have the significant impact and an issue of their choice remains opened and actual in the framework of the task.

Prohibition of Monopolistic Practices in Business Trials in Indonesia: Reforming on Business Competition Supervisory Commission

Indonesia recognizes the importance of fair competition for economic growth and consumer welfare. To ensure a level playing field, the country has established legislation and regulations that prohibit monopolistic practices and promote healthy competition. Key laws include the Indonesian Anti-Monopoly Law and the Law on Business Competition Supervision and Control. Business trials play a crucial role in enforcing these laws. Courts serve as arbiters in cases involving alleged monopolistic practices, employing thorough examinations of evidence, expert testimonies, and legal arguments presented by the parties involved. The burden of proof rests on the plaintiff, who must demonstrate the existence of anti-competitive behavior and its adverse effects on the market. The Prohibition of Monopolistic Practices in Business Trials in Indonesia encompasses various types of anti-competitive conduct, such as price fixing, market division, and abuse of dominant market position. Violations of these laws can result in significant penalties, including substantial fines, dissolution of companies, and criminal charges for individuals involved. To strengthen the effectiveness of business trials, Indonesia has established regulatory bodies such as the Business Competition Supervisory Commission (KPPU). The KPPU plays a crucial role in investigating alleged violations, providing recommendations to the courts, and monitoring compliance with rulings. Despite the robust legal framework, challenges remain in enforcement. Collaboration between government agencies, the judiciary, and the business community is essential. Additionally, monitoring and updating the legal framework to address evolving market dynamics and emerging forms of anti-competitive practices are necessary.

Position Fixing and Uncertainty

Position Fixing and Uncertainty

GNSS/IMU Sensor Fusion Performance Comparison of a Car Localization in Urban Environment Using Extended Kalman Filter

Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) are popular navigation sensor for position fixing technique and dead reckoning system that complement each other. GNSS can provide accurate position and velocity information when it establishes a Line of Sight (LOS) with a minimum of four satellites. However, this accuracy can decrease due to signal outage, jamming, interference, and multipath effects. On the other hand, the IMU has the advantage of measuring the platform’s orientation with a high-frequency update and is not affected by environmental conditions. However, a drift effect causes the measurement errors to accumulate. Several studies have demonstrated the fusion of both sensors in terms of the Extended Kalman Filter (EKF). This study conduct sensor fusion for car localization in an urban environment based on the loosely coupled integration scheme. In order to improve the sensor fusion performance, pre-processing GNSS and IMU data were applied. The result shows that pre-processing DGNSS and IMU filtering can increase the accuracy of the integrated navigation solution up to 80.02% in the east, 80.13% in the north, and 89.45% in the up direction during the free outage period.

Conditional Dependencies and Position Fixing

Experimental crude datasets are usually processed with statistical methods to obtain rough evaluations of nautical measurements. Taking the observations and rectifying the knowledge on them are not correlated. In modern computer applications, raw datasets are usually exploited in the initial learning phase. At this stage, the available data are explored to extract the necessary parameters required within the scheme of computations. The aim of this study was to undertake the crude data processing problem to extract the conditional dependencies that appear as the most important factors when handling the distorted data. First, I upgraded the traditional structures, which are histograms. The stepwise diagrams feature their uncertain evaluation. I upgraded the hierarchy among the evidence within the data pool and defined the given ranking adequate membership functions. The principles of fuzzy systems justified the use of the bin-to-bin additive approach to obtain the locally injective density functions, which can be perceived of as conditional dependency diagrams that enable the construction of simple belief assignments. The structural combination includes the solution to the position fixing problem.

Two sixteenth-century nautical charts of the South Atlantic Ocean: an early example of cartography used at sea

AbstractDespite the crucial role played by nautical cartography during the 16th-century Iberian Expansion, surviving examples of charts used at sea are extremely rare, leaving gaps in our knowledge of how they were used in practice during this pivotal period. The present paper sheds light on this matter by introducing one of earliest extant Portuguese charts presenting positional fixes, which have so far gone unnoticed by researchers: the anonymous chart of about 1524 kept at the James Ford Bell Library. It is demonstrated that a second chart, kept at the Harry Ransom Center, was made by the same author from the same pattern. The production context of the charts is evidenced through a description of the manuscript copying technique most likely employed, and the rules governing chart manufacture in 16th-century Portugal. Exceptional aspects of the charts’ placenames are discussed, and a possible source for their geographical design is identified.

Evolution of Maritime GNSS and RNSS Performance Standards

The primary means for electronic position fixing in use in contemporary maritime transport are shipborne GPS (Global Positioning System) receivers or DGPS (Differential GPS) receivers. More advanced GNSS (Global Navigation Satellite System) or RNSS (Regional Navigation Satellite Systems) receivers are able to process combined signals from American GPS, Russian GLONASS, Chinese Beidou (BDS), European Galileo, Indian IRNSS, and Japan QZSS. Satellite-based augmentation systems (SBAS) are still not commonly used in the maritime domain, especially onboard vessels certified under international SOLAS convention. The issues and weaknesses of existing International Maritime Organization recommendations, guidelines, requirements, performance standards, and policies on GNSS shipborne sensors are discussed and presented in the paper. Many problems that have already been dealt with in other means of transportation are still to be solved in the maritime domain. The integrity monitoring is addressed as the main issue, and recommendations based on solutions implemented in aviation and the latest research are proposed. Finally, the strengths, weaknesses, opportunities, and threats awaiting maritime GNSS standardization process are outlined.

A Position Fixing Method for Near-Bottom Camera Data on the Seafloor

The submarine camera system is one of the most effective detection methods for detecting seabed hydrothermal sulfide. The position fixing of camera equipment is generally achieved by the ultra-short baseline (USBL) positioning systems. The dynamic changes in the marine environment and the loss of acoustic signals lead to many abnormal points in the USBL positioning data. The existing methods cannot perform position fixing correction for USBL positioning data with many scattered abnormal points. This paper selects and focuses on the seabed camera data of the XunMei mineralization area acquired from the China South Atlantic voyage and employs the DTW optimization algorithm to solve this problem. This method is implemented based on Python language and an ArcGIS technical environment, and a total of 97,469 topographic profiles with 10 m spacing are extracted from the topographic data of the object area with 1m accuracy. Moreover, the highest similarity (95.9%) is obtained between the bathymetric profile of the camera survey line and the above topographic profile. The results indicate that the proposed algorithm is fast and effective, and the positioning correction accuracy of the deep-sea near-bottom camera data can reach the meter level (determined by the topographic data accuracy). Moreover, the solution can provide services for accurately position fixing near-bottom exploration equipment and its exploration data. It can also solve the problem of underwater position fixing problem that a GPS cannot solve.

Position fixing with cold atom gravity gradiometers

This paper proposes a position fixing method for autonomous navigation using partial gravity gradient solutions from cold atom interferometers. Cold atom quantum sensors can provide ultra-precise measurements of inertial quantities, such as acceleration and rotation rates. However, we investigate the use of pairs of cold atom interferometers to measure the local gravity gradient and to provide position information by referencing these measurements against a suitable database. Simulating the motion of a vehicle, we use partial gravity gradient measurements to reduce the positional drift associated with inertial navigation systems. Using standard open source global gravity databases, we show stable navigation solutions for trajectories of over 1000 km.

Diurnal increases in depths of humpback whale (Megaptera novaeangliae) mother‐calf pods off West Maui, Hawaiʻi: A response to vessels?

AbstractStudies of humpback whale (Megaptera novaeangliae) habitat use in their Hawaiian breeding grounds have revealed that mother‐calf pairs favor shallow waters to avoid harassment from males. However, human activity in these same waters may exert an opposing force on habitat use. To investigate this hypothesis, instantaneous scan samples of whale and vessel distribution were collected from West Maui, Hawaiʻi. Theodolite position fixes were combined with GIS techniques to determine the depths and seabed terrain type occupied by 161 humpback whale pods containing a calf (calf pods) and 872 pods without a calf (noncalf pods). We found no significant diurnal trends for noncalf pods, but calf pods occupied progressively deeper water over the course of each day. There was no evidence that this shift was related to (1) a “spillover” resulting from high mother‐calf density in shallow water, (2) harassment by males occupying the same space as mother‐calf pairs, or (3) the presence of mainly older and larger calves. However, while diurnal trends of whale‐watching vessels largely mirrored those of mother‐calf pods, nonwhale‐watching vessels tended to remain in shallower waters throughout the day. These results suggest that nearshore vessels may negatively impact the natural preference of mother‐calf pairs for shallow waters.

GNSS Independent Position Fixing using Multiple Navigational Features Registration

Safe navigation at sea depends on reliable position information. The easy to use and readily available navigation satellite systems are providing round the clock position information for seafarers, but denial of these services by jamming or spoofing techniques have become frequent, and other means are needed to validate critical navigation information. This paper revisits traditional methods to estimate position and heading of a vessel and offers a framework for computerized calculation of these basic observables without the use of radio-borne external information. Using radar and sea chart information, the paper investigates the quality of navigation information based on observed location of beacons, landmarks, coastlines and buoys. The paper demonstrates convincing accuracy in both position and heading estimation.

Assessing the Role of Sampling Uncertainty When Predicting Behavioral Responses of Tagged Cetaceans Exposed to Naval Sonar

Concerns over cetacean mortality events coincident with maritime warfare exercises have motivated efforts to characterize the effects of anthropogenic noise on free-ranging whales and dolphins. By monitoring the movement, diving, and acoustic behaviors of individual whales before, during, and after sound exposure, behavioral response studies (BRSs) have supported significant progress in our understanding of the sensitivity of various cetacean species to high-powered naval sonar signals. However, differences in the designs and sampling capabilities of animal-borne tags typically used in BRS experiments prompt questions about the influence of data resolution in quantitative assessments of noise impacts. We conducted simulations to examine how uncertainty in the acoustic dose either measured on high-resolution multi-sensor biologging tags or modeled from position-transmitting satellite telemetry tags may affect predictions of behavioral responses in Cuvier’s beaked whales (Ziphius cavirostris) exposed to low- and mid-frequency active sonar. We considered an array of scenarios representative of real-world BRSs and used posterior estimates of dose-response functions obtained under an established Bayesian hierarchical modeling framework to explore the consequences of different tag choices for management decision-making. Our results indicate that (1) the zone of impact from a sonar source is under-estimated in most test conditions, (2) substantial reductions in the uncertainty surrounding dose-response relationships are possible at higher sample sizes, and (3) this largely holds true irrespective of tag choice under the scenarios considered, unless positional fixes from satellite tags are consistently poor. Strategic monitoring approaches that combine both archival biologging and satellite biotelemetry are essential for characterizing complex patterns of behavioral change in cetaceans exposed to increasing levels of acoustic disturbance. We suggest ways in which BRS protocols can be optimized to curtail the effects of uncertainty.

The Improvement of Wireless Sensor Networks Node Location Algorithm in Extreme Environment

WSN is a wireless network composed of quantities of sensor nodes in a self-organizing multi-hop mode. Its used for perceive, collect and handling the information data to the monitoring center or the terminal user, to realize the communication between “people and things” and “things and things”. Among them, position fixing technology is the basic technology of many applications of WSN. The using of sensor nodes for positioning is very valuable in many practical applications. This paper introduces a modified DV-Hop location algorithm without range measurement, which has the characteristics of high positioning accuracy, low cost, low energy consumption, etc., and has important practical significance. The simulation results show that the positioning accuracy will be higher, because the process is easy to improve the calculation, does not need to add additional hardware, so it has a strong applicability.

Hybrid Tightly-Coupled SINS/LBL for Underwater Navigation System

The application of long baseline aided strap-down inertial navigation system (SINS/LBL) has been demonstrated to be an effective solution for accumulative position errors of underwater vehicles (UVs). To address the inefficient positioning when available hydrophones are few in acoustic array, a hybrid tightly-coupled SINS/LBL is presented for underwater navigation system. The system is composed of SINS, LBL and pressure sensor (PS). The hybrid positioning model based on slant range, slant-range rate, slant-range difference and slant-range rate difference is established according to the location principle of time of arrival (TOA) and time difference of arrival (TDOA) when the number of available hydrophones is two. TDOA positioning model based on slant-range difference and slant-range rate difference is adopted when the number of available hydrophones is more than two. The two tightly-coupled SINS/LBL models could be switched with each other as the number of available hydrophones changes in acoustic array. This paper used experimental data obtained from an unmanned surface vehicle (USV) to validate the navigation performance. Compared with single tightly-coupled SINS/LBL model, the proposed method can provide faster error convergence and more accurate submerged position fixes.