GPS in autonomous underwater vehicles

Bird attitudes, with roll, pitch, and yaw angles, are required for modeling the measured electromagnetic response of the earth. Global Positioning System (GPS) antennas can be used in airborne electromagnetic (AEM) systems to monitor airborne platform attitude and bird maneuver. We have found evidence from photographic sequences that four GPS antennas, three on the bird and one on the aircraft, generally are adequate for angular and altitude geometry control. The mounting system for the bird frame introduces vibration noise. We have developed a model that predicts bird maneuver from the use of GPS antennas already present during routine airborne surveys. The bird motion, whether inline or crossline, is modeled from the difference between the aircraft location and the mean location of the bird. This also accurately predicts the roll of the bird when an inline yoke mounting is used. The minimum number of GPS antennas required to monitor the motion of a cylindrical electromagnetic (EM) bird typical of frequency-domain systems is two, one on the aircraft and one on the bird. We have defined optimum locations of GPS antennas to enable geometric monitoring of towed-bird systems. The findings suggest that the bird be mounted with two aerodynamically efficient GPS antennas, one on the nose and one on the tail. This enables the measurement of the pitch and yaw of the bird, with roll deduced using the third GPS on the helicopter.

Bird attitudes, with roll, pitch, and yaw angles, are required for modeling the measured electromagnetic response of the earth. Global Positioning System (GPS) antennas can be used in airborne electromagnetic (AEM) systems to monitor airborne platform attitude and bird maneuver. We have found evidence from photographic sequences that four GPS antennas, three on the bird and one on the aircraft, generally are adequate for angular and altitude geometry control. The mounting system for the bird frame introduces vibration noise. We have developed a model that predicts bird maneuver from the use of GPS antennas already present during routine airborne surveys. The bird motion, whether inline or crossline, is modeled from the difference between the aircraft location and the mean location of the bird. This also accurately predicts the roll of the bird when an inline yoke mounting is used. The minimum number of GPS antennas required to monitor the motion of a cylindrical electromagnetic (EM) bird typical of frequency-domain systems is two, one on the aircraft and one on the bird. We have defined optimum locations of GPS antennas to enable geometric monitoring of towed-bird systems. The findings suggest that the bird be mounted with two aerodynamically efficient GPS antennas, one on the nose and one on the tail. This enables the measurement of the pitch and yaw of the bird, with roll deduced using the third GPS on the helicopter.

The paper is dealing with auto (cross) correlation properties of global positioning system (GPS) codes and their vulnerability to noise, taking into account the current status of GPS space segment and the needs for additional allocation of GPS codes, as a consequence of increasing number of navigation satellites in space segment. This material describes the models, generation and the characteristics of the Gold codes from PRN 38 to PRN 45, that are not used in GPS Navstar. Therefore, the properties of these last 8 possible codes obtained with a 10-bit linear feedback shift registers (LFSR) were analyzed and a comparison with previously used GPS C/A codes PRN 1 to 37 was performed.

The strapdown inertial navigation system is usually employed to determine the attitude, velocity and position of an autonomous underwater vehicle (AUV) for its specific advantage of small volume. The navigation accuracy provided by the SINS which employs accelerometers and gyroscopes deteriorates with time. Consequently, an external aiding source such as global positioning system (GPS) can be employed to reduce the error growth in the SINS. The GPS aided SINS system provides enhanced positioning accuracy of the AUV compared to that of a standalone SINS technique. A new method based on Kalman filtering and RBF neural network to fuse the GPS and the SINS data for an AUV application was presented in this paper. It was proved from the experiments that navigation accuracy was improved substantially between GPS position fixes with the proposed method.

This study investigated long-term land subsidence derived from borehole extensometer and Global Positioning System (GPS) observations from Addicks, a suburb located in West Houston, Texas. The Addicks borehole extensometer was built in 1974 by the USGS. Two GPS stations were installed at this site in 1993 and 1996, respectively. One GPS antenna (ADKS) is mounted on the inner pipe of the extensometer borehole, which is firmly anchored 549 m below the land surface. Another GPS antenna (PA05) is mounted on a permanent antenna pole anchored 6 m below the land surface. The horizontal distance between these two GPS antennas is 50 m. Continuous GPS data collected from the deeply anchored GPS antenna indicate that the bottom of the borehole has been stable over the past 20 years (1993–2012). Hence the compaction derived from the borehole extensometer data represents the total subsidence at this site, which should be approximately equivalent to the vertical displacement (subsidence) recorded by the shallowly anchored GPS antenna (PA05). In this study, the vertical displacement time series recorded by the shallowly anchored GPS antenna are regarded as the true values to assess the accuracy of the subsidence time series recorded by the extensometer. The authors' analysis indicates that the difference between the cumulative subsidence measured by the extensometer and the GPS antenna (PA05) is less than 5 mm for a 17-year span (1996–2012). The RMS of the residuals of the monthly subsidence time series derived from the extensometer and GPS antenna (PA05) data over 13 years (2000–2012) is 2 mm.

The Global Positioning System (GPS) has been used in a variety of applications for which new and more restrictive requirements in the design of the receiving antenna have been introduced. In particular, for high-precision GPS applications, a receiving antenna with superior rejection to multipath signals is required. Furthermore, in order to satisfy the demanded precision and reliability, a high performance GPS antenna must be capable of operation at the two GPS frequencies (1.57542 GHz and 1.2276 GHz). One effective design (see Boccia, L. et al., Microwave and Optical Technology Letters, 2001) demonstrates that consistent multipath mitigation can be obtained with a single frequency shorted annular patch. A stacked shorted elliptical patch, operating at the two GPS bands, is presented. The antenna combines the shorted ring radiation properties, which have proved to comply adequately with multipath mitigation requirements, with dual frequency operations, resulting in a compact high performance dual frequency GPS antenna.

This paper presents an adaptive learning method for data fusion in autonomous\ndriving vehicles. The localization is based on the integration of Inertial\nMeasurement Unit (IMU) with two Real-Time Kinematic (RTK) Global Positioning\nSystem (GPS) units in an adaptive Kalman filter (KF). The observability\nanalysis reveals that $i$) integration of a single GPS with IMU does not\nconstitute an observable system; $ii$) integration of two GPS units with IMU\nresults in a locally observable system provided that the line connecting two\nGPS antennas is not parallel with the vector of the measured acceleration,\ni.e., the sum of inertial and gravitational accelerations. The latter case\nmakes it possible to compensate for the error in the estimated orientation due\nto gyro drift and its bias without needing additional instruments for absolute\norientation measurements, e.g., a magnetic compass. Moreover, in order to cope\nwith the fact that GPS systems sometimes lose their signal and receive\ninaccurate position data, the self-tuning filter estimates the covariance\nmatrix associated with the GPS measurement noise. This allows the KF to\nincorporate GPS measurements in the data fusion process heavily only when the\ninformation received by GPS becomes reliably available.\n

To improve the navigation accuracy of AUV (autonomous underwater vehicle), SINS (strapdown inertial navigation system), GPS (global positioning system), DVL (Doppler velocity log) and TAN (terrain aided navigation) are adopted in the AUV integrated navigation system. The mathematic model of the AUV integrated navigation system and the observation model of the chosen navigation sensors are built according to the system simulation experiments data. An improved filter based on RBF neural network for adjusting the information sharing factors is designed and implemented in the AUV integrated navigation system. Simulation experiments are carried out according to the mathematic model. It can be concluded from the simulation experiments that the navigation accuracy is improved substantially with the multiple sensors and federated filter in case that colored noise is engaged. The novel integrated navigation system is effective in prohibiting the divergence of the filter and improving fault tolerance ability and it greatly raises the precision of the navigation accuracy for the AUV integrated navigation system.

The absence of global positioning system (GPS) signals and the influence of ocean currents are two of the main challenges facing the autonomy of autonomous underwater vehicles (AUVs). This paper proposes an acoustic localization-based tracking control method for AUVs. Particularly, three buoys that emit acoustic signals periodically are deployed over the surface. Times of arrivals of these acoustic signals at the AUV are then obtained and used to calculate an estimated position of the AUV. Moreover, the uncertainties involved in the localization and ocean currents are handled together in the framework of the extended Kalman filter. To deal with system physical constraints, model predictive control relying on online repetitive optimizations is applied in the tracking controller design. Furthermore, due to the different sampling times between localization and control, the dead-reckoning technique is utilized considering detailed AUV dynamics. To avoid using the highly nonlinear and complicated AUV dynamics in the online optimizations, successive linearizations are employed to achieve a trade-off between computational complexity and control performance. Simulation results show that the proposed algorithms are effective and can achieve the AUV tracking control goals.

As the exploration of marine resources continues to deepen, the utilization of Autonomous Underwater Vehicles (AUVs) for conducting marine resource surveys and underwater environmental mapping has become a common practice. In order to successfully accomplish exploration missions, AUVs require high-precision underwater navigation information as support. A Strapdown Inertial Navigation System (SINS) can provide AUVs with accurate attitude and heading information, while a Doppler Velocity Log (DVL) is capable of measuring the velocity vector of the AUVs. Therefore, the integrated SINS/DVL navigation system can furnish the necessary navigational information required by an AUV. In response to the issue of DVL being susceptible to external environmental interference, leading to reduced measurement accuracy, this paper proposes an end-to-end deep-learning approach to enhance the accuracy of DVL velocity vector measurements. The utilization of the raw measurement data from an Inertial Measurement Unit (IMU), which includes gyroscopes and accelerometers, to assist the DVL in velocity vector estimation and to refine it towards the Global Positioning System (GPS) velocity vector, compensates for the external environmental interference affecting the DVL, therefore enhancing the navigation accuracy. To evaluate the proposed method, we conducted lake experiments using SINS and DVL equipment, from which the collected data were organized into a dataset for training and assessing the model. The research results show that the DVL vector predicted by our model can achieve a maximum improvement of 69.26% in terms of root mean square error and a maximum improvement of 78.62% in terms of relative trajectory error.

The multi-band frequency operation is a property that antennas, utilized in several communication systems, have to exhibit. In this paper, a compact printed antenna for Global Positioning System (GPS) and terrestrial radio services is presented. It is composed via the union of four inverse Koch fractal patches. The antenna operates in three frequency ranges (GPS, Digital Cellular System-DCS1800 and 2.7 GHz). It is driven by two feed probes, directly matched to the radiating element without any matching network to be necessary. At GPS, the antenna is capable of generating a circularly polarized field, with maximum strength at the broadside direction. At the other two frequencies, the field is linearly polarized and the maximum of radiation appears apart from the broadside. Two pins, embedded in the structure, are activated at DCS and at 2.7 GHz in order to enhance the performance of the antenna.

A real-time integrated navigation system with 2-cm position accuracy was developed using commercial off-the shelf (COTS) equipment including inertial sensors and differential Global Positioning System (GPS) receivers, and was demonstrated for transportation applications with an emphasis on lane departure detection. A 900-MHz radiofrequency communications link transmits GPS base station range and carrier phase measurements to a GPS receiver on the vehicle. The GPS receiver calculates the vehicle position relative to the surveyed base location. The loosely coupled eight-state extended Kalman filter with 10-Hz navigation aids provides smoothed position information between 2-Hz GPS updates and provides graceful degradation in the presence of GPS blockages or communication dropouts. Currently, the navigation aids include anti-lock braking system wheel turns, electronic compass heading and pitch, and map vertical height. Data acquisition and Kalman filtering systems were developed to handle real-time processing and recording of all instrument data for further post-test system evaluation to determine the optimum configuration. An accurate rapid survey and map representation approach for measuring lane boundaries was validated using a vehicle, demonstrating inherit repeatability by the GPS positioning system. Real-time lane departure monitoring was developed. A video camera was installed to assist in accurate surveying and real-time system validation. This GPS-based positioning system is suitable for highway speeds during all weather conditions. It can be extended to other collision avoidance, drowsy driver awareness, advanced curve or intersection warnings, SOS, tracking, automated control, fast precision road mapping, and traffic management applications.

With the Global Positioning System (GPS), it is possible to estimate the baseline vectors between several GPS antennas (with fixed positions on a vehicle) and so, the attitude can be determined. To achieve this, the precise carrier phase measurements are used, however, these measurements have the so called phase ambiguities (integer number of cycles) that need to be solved. When only single-frequency measurements (L1 band) are used, the method known as Ambiguity Filter is employed, after the search method LAMBDA, to stabilize the obtained solution. The leverage of the Ambiguity Filter, relatively to the alternative of using only the LAMBDA method, comes from using a prior knowledge of the baseline length in the ambiguity resolution problem, which the LAMBDA does not. Preliminary tests with the implementation of the Ambiguity Filter have shown that its performance is very sensitive to the precision with which the baseline length is known. This was the main motivation for the work here presented. The results presented in this paper are based on field tests, conducted at the university campus, with two GPS receivers in a static, fixed length, baseline configuration.

Many vehicular emergency call applications utilize a dual-band cellular phone for data exchange and Global Positioning System (GPS) antenna for localization. When the cellular phone antenna is transmitting in close proximity to the GPS antenna, the GPS low-noise amplifier (LNA) is expected to be not affected, i.e., remain linear during the operation. Most commercial GPS LNAs hardly meet this requirement, hence passive antenna-to-antenna isolation and preamplifier filtering without affecting the noise figure of the system becomes crucial. In addition, passive antenna gain requirements for emergency call applications are generally higher than those of regular dual-band cellular phone antennas. To satisfy all these requirements, a multiple-element antenna is designed, built, and measured.

Many possible autonomous underwater vehicle (AUV) missions require a high degree of navigational accuracy. The Global Positioning System (GPS) is capable of providing this accuracy. However, intermittent reception caused by either wave action or deliberate submergence will cause the loss of GPS position fix information for periods extending from several seconds to minutes. The SANS system is designed to demonstrate the feasibility of using a low-cost strapped-down inertial measurement unit to navigate between GPS fixes. It is anticipated that navigational accuracy comparable to GPS is possible between fixes.