Showing papers on "GPS/INS published in 2006"

Sigma-point Kalman filtering for integrated GPS and inertial navigation

Abstract: A sigma-point Kalman filter is derived for integrating GPS measurements with inertial measurements from gyros and accelerometers to determine both the position and the attitude of a moving vehicle. Sigma-point filters use a carefully selected set of sample points to more accurately map the probability distribution than the linearization of the standard extended Kalman filter (KKF), leading to faster convergence from inaccurate initial conditions in position/attitude estimation problems. The filter formulation is based on standard inertial navigation equations. The global attitude parameterization is given by a quaternion, while a generalized three-dimensional attitude representation is used to define the local attitude error. A multiplicative quaternion-error approach is used to guarantee that quaternion normalization is maintained in the filter. Simulation and experimental results are shown to compare the performance of the sigma-point filter with a standard EKF approach.

Cooperative Localization for Autonomous Underwater Vehicles

Abstract: This paper describes an algorithm for distributed acoustic navigation for A utonomous Underwater Vehicles (AUVs). Whereas typical AUV navigation systems utilize pre-calibrated ar rays of static transponders, our work seeks to create a fully mobile network of AUVs that perform acoustic rang ing and data exchange with one another to achieve cooperative positioning for extended duration missions over lar ge areas. The algorithm enumerates possible solutions for the AUV trajectory based on dead-reckoning and range-o ly measurements provided by acoustic modems that are mounted on each vehicle, and chooses the trajectory via minimizatio n of a cost function based on these constraints. The resulting algorithm is computationally efficient, meets the stric t bandwidth requirements of available AUV modems, and has potential to scale well to networks of large numbers of vehicles. The method has undergone extensive experimentation, and results from three different scenario s re reported in this paper, each of which utilizes MIT SCOUT Autonomous Surface Craft (ASC) as convenient platform s for testing. In the first experiment, we utilize three ASCs, each equipped with a Woods Hole acoustic modem, as surrog ates for AUVs. In this scenario, two ASCs serve as Communication/Navigation Aids (CNAs) for a third ASC that compu tes its position based exclusively on GPS positions of the CNAs and acoustic range measurements between platf orms. In the second scenario, an undersea glider is used in conjunction with two ASCs serving as CNAs. Finally, in the third e xperiment, a Bluefin12 AUV serves as the target vehicle. All three experiments demonstrate the succ s ful operation of the technique with real ocean data. Index Terms autonomous underwater vehicles, cooperative navigation, mobile robo tics, sensor networks I. I NTRODUCTION The absence of Global Positioning System (GPS) signals unde rwat r makes navigation for Autonomous Underwater Vehicles (AUVs) a difficult challenge. Without an exte rnal reference in the form of acoustic beacons at known positions, the vehicle has to rely on proprioceptive inform ation obtained through a compass, a Doppler Velocity Logger (DVL) or an Inertial Navigation System (INS) [WYSH00] . Independent of the quality of the sensors used, the error in the position estimate based on dead-reckoning i formation grows without bound. Typical navigation The authors are with the Computer Science and Artificial Intel lig nce Laboratory, Massachusetts Institute of Technolog y, Cambridge, MA 02139, USA October 30, 2008 DRAFT 2 errors are 0.5 % to 2 % of distance traveled for vehicles opera ting within a few hundred meters of the sea floor such that their DVL has a lock on the bottom. Errors as low as 0. 1 % can be obtained with large and expensive INS systems, but for vehicles relying only on a compass and a s peed estimate, errors can be as high as 20 %. By surfacing the AUV can obtain a position update through its GP S, but this is impossible (under ice) or undesirable for many applications. The use of static beacons in the form o f a Long Baseline (LBL) array limits the operation area to a few km and requires a substantial deployment effort before operat ions, especially in deep water. As underwater vehicles become more reliable and affordable the simultaneous use of several AUVs recently became a viable option and multi-vehicle deployments will b ecome standard in the upcoming years. This will not only make possible entirely new types of missions which r ely on cooperation, but will also allow each individual member of the group to benefit from navigation inf ormation obtained from other members. For optimal cooperative localization a few dedicated Communication an d Navigation Aid-AUVs (CNAs), which maintain an accurate estimate of their position through sophisticated DVL and INS sensors, can enable a much larger group of vehicles with less sophisticated navigation suites to main tain an accurate position, as described in [VLCW04a]. The idea of an underwater equivalent to the terrestrial GPS h as long held appeal to AUV researchers. For example, A.C.S.A. has developed a portable undersea tracking range t hat provides a form of “underwater GPS” in a local area [Tho01]. In the A.C.S.A. system, a network of four surfa ce buoys equipped with GPS and RF communications utilize passive acoustic range measurements to track the po sition of a time-synchronized mobile undersea device. While the base system usually employs moored or drifted surfa ce buoys, experiments using self-powered surface craft have also been performed. Further extensions of this c oncept could employ acoustic communications to relay the vehicle pose estimate obtained by the surface buoys back to the undersea vehicle itself. The motivation behind our research is to enable multiple AUV s to cooperatively navigate. The ideal solution would enable heterogeneous teams of AUVs to operate with hig navigational precision, without frequent surfacing for GPS measurements, even for the case when only a small numb er of the AUVs in the team are equipped with expensive inertial sensors. One application of this capabi lity would be to perform rapid, large-area search with a mixed AUV network consisting of Comm/Nav-Aid AUVs, Search -Classify-Map AUVs, and Reacquire-Identify AUVs [VLCW04b]. The problem of cooperative navigation of AUVs is highly inte rconnected to the problem of undersea acoustic communications [Cat90], [KB00], [FJG 01]. Our work capitalizes on recent progress by the Acoustic Modem Group at Woods Hole Oceanographic Institution (WHOI) in deve loping integrated communication and navigation (ranging) capabilities for small AUVs. This application ra ises several interesting challenges for acoustic telemetr y research, such as the need to handle a fully mobile network an d the goal of achieving accurate one-way ranging through stable clock synchronization. There has been a great deal of work in terrestrial settings on the problem of cooperative navigation of multiple mobile robots. Often the problem is cast in terms of a mix of mo bile and static nodes in a large-scale sensor network, with either angle-only or range-only measurement s. A variety of state estimation approaches have been followed, including Markov chain Monte Carlo and set-theor etic state estimators. For example, Liao et al. [LHDS06] October 30, 2008 DRAFT 3 employed a particle filter state estimator for cooperative l oca ization of multiple ground robots using range-only measurements. Djugash et al. [DKSZ06] developed an approach that integrated Simultaneo us Localization and Mapping (SLAM) with mobile sensor networks, achieving self -calibration of a network consisting of mobile and stationary nodes with range measurements. Grocholsky et al. [GSSK06] used nonlinear set-based state estimation techniques for localization of multiple mobile robots with range measurements between platforms. The underwater setting presents some unique challenges for cooperative mobile robotics. The assumption of a fast and reliable communication channel between all parti cipants of the cooperative navigation effort, as made in [RB00], [RDM02], and [MLRT04], does not hold underwater. Due to the strong attenuation of electro-magnetic waves underwater, radio or optical communication is not pra ctic lly feasible except for distances of a few meters. As a result acoustic modems, typically operating between 15 and 30 kHz, provide the only possible means of communicating at long ranges underwater. Data rates are typ ically several orders of magnitude below those achieved with radio-based communication channels [KB00]. With soun d propagation being dependent on temperature and salinity, which can both vary strongly within the water colu mn, the acoustic communication channel is unreliable and its performance hard to predict. This is especially true in shallow water, where severe multi-path is often encountered. The concept of portable landmarks as outlined in [KNH94] is not feasible as it is often difficult for an AUV to hold its position, especially in strong currents. The objective for our work is to develop and test an algorithm for cooperative positioning of multiple mobile undersea vehicles that can use acoustic modems concurrentl y for both ranging and for communication [FJG 01]. The solution must be robust to the errors and time delays that are inherent to acoustic range measurements and must take into account the severe bandwidth constraints of state -of-the-art undersea acoustic modems. This restriction prevents the transfer of full state information between veh icl s. The cooperative navigation problem is complementary to the problems of cooperative motion planning and control for underwater platforms. For example, Leonard et al. have addressed a class of cooperative adaptive sampling problems for networks of AUVs and underwater gliders [LPL 07]. In this work the motion of a fleet of vehicles is directed to acquire optimal data sets based on the predict ions of numerical ocean models. This work typically assumes that accurate navigation information is available , for example through GPS measurements obtained at the surface. This scenario provides a compelling application s cenario in which our cooperative navigation techniques could be applied, obviating the need for all vehicles in the fl e t to surface for positioning. Using a one-way messaging system with the WHOI modem, Eustice et al. [EWSG07] recently implemented a least squares version of a maximum likelihood algorithm to c arry out moving baseline navigation. The approach utilized a particularly accurate heading and dead-reckoni ng system and as well as a specially designed low drift timing clock. II. T ECHNICAL APPROACH In order to cooperate during their mission the AUVs will be ou tfitted with acoustic modems. Data rates on the order of 100 bytes/s over distances of up to 5 km have been a chieved, but given varying channel quality, October 30,

Integrated GPS/INS System for Pedestrian Navigation in a Signal Degraded Environment

Abstract: This paper evaluates the performance of a shoe/foot mounted inertial system for pedestrian navigation application. Two different grades of inertial sensors are used, namely a medium cost tactical grade Honeywell HG1700 inertial measurement unit (IMU) and a low-cost MEMS-based Crista IMU (Cloud Cap Technology). The inertial sensors are used in two different ways for computing the navigation solution. The first method is a conventional integration algorithm where IMU measurements are processed through a set of mechanization equation to compute a six degree-offreedom (DOF) navigation solution. Such a system is referred to as an Inertial Navigation System (INS). The integration of this system with GPS is performed using a tightly coupled integration scheme. Since the sensor is placed on the foot, the designed integrated system exploits the small period for which foot comes to rest at each step (stance-phase of the gait cycle) and uses Zero Velocity Update (ZUPT) to keep the INS errors bounded in the absence of GPS. An algorithm for detecting the stance-phase using the pattern of three-dimensional acceleration is discussed. In the second method, the navigation solutions is computed using the fact that a pedestrian takes one step at a time, and thus positions can be computed by propagating the step-length in the direction of pedestrian motion. This algorithm is termed as pedestrian dead-reckoning (PDR) algorithm. The IMU measurement in this algorithm is used to detect the step, estimate the step-length, and determine the heading for solution propagation. Different algorithms for stridelength estimation and step-detection are discussed in this paper. The PDR system is also integrated with GPS through a tightly coupled integration scheme. The performance of both the systems is evaluated through field tests conducted in challenging GPS environments using both inertial sensors. The specific focus is on the system performance under long GPS outages of duration upto 30 minutes.

Comparison of Vector-Based Software Receiver Implementations With Application to Ultra-Tight GPS/INS Integration

Abstract: This paper investigates three different Kalman filter implementation options to estimate signal tracking errors in a GPS receiver with particular emphasis given to the carrier phase. The three options are outlined in terms of the system and measurement models. Initial assessment of the different options is performed in scalar-tracking mode with strong signals to assess their relative carrier phase tracking performance. Each option is then evaluated in vector-tracking mode both with strong signals collected in the field and with attenuated signals collected with a hardware GPS simulator. Results indicate that only two of the three options are able to track incoming signals in vector-tracking mode. Furthermore, both options are shown to be able to track the carrier phase up to an attenuation of about 15 dB and still maintain a velocity solution accurate to a few centimeters per second.

Method and system for attitude determination of a platform using global navigation satellite system and a steered antenna

Abstract: A system and method for determining the attitude of a platform is provided. The method includes: (a) Searching and scanning for one or more GPS satellite(s) to determine initial platform position; wherein a single directionally steered antenna scans for the GPS/GNSS satellite; (b) pointing and scanning the antenna to GPS/GNSS satellite to determine a first angular measurement of a direction of a GPS/GNSS signal; (c) measuring carrier to noise ratio of the GPS/GNSS satellite; (d) dithering the single directionally steered antenna to obtain an angular measurement relative to an antenna pattern bore-sight reference; (e) repeating steps (b)-(d) to determine a second angular measurement of the direction of a second GPS signal; (f) determining the attitude error of the platform using the first and second angular measurements; (g) updating the platform position and attitude.

The Utilization of Artificial Neural Networks for Multisensor System Integration in Navigation and Positioning Instruments

Abstract: Inertial-navigation system (INS) and global position system (GPS) technologies have been widely applied in many positioning and navigation applications. INS determines the position and the attitude of a moving vehicle in real time by processing the measurements of three-axis gyroscopes and three-axis accelerometers mounted along three mutually orthogonal directions. GPS, on the other hand, provides the position and the velocity through the processing of the code and the carrier signals of at least four satellites. Each system has its own unique characteristics and limitations. Therefore, the integration of the two systems offers several advantages and overcomes each of their drawbacks. The integration of INS and GPS is usually implemented utilizing the Kalman filter, which represents one of the best solutions for INS/GPS integration. However, the Kalman filter performs adequately only under certain predefined dynamic models. Alternatively, this paper suggests an INS/GPS integration method based on artificial neural networks (ANN) to fuse uncompensated INS measurements and differential GPS (DGPS) measurements. The proposed method suggests two different architectures: the position update architecture (PUA) and the position and velocity PUA (PVUA). Both architectures were developed utilizing multilayer feed-forward neural networks with a conjugate gradient training algorithm

Bridging GPS outages using neural network estimates of INS position and velocity errors

Abstract: INS and GPS are commonly integrated using a Kalman filter (KF) to provide a robust navigation solution, overcoming situations of GPS satellite signals blockage. This research presents an alternative method of bridging GPS outages requiring no prior knowledge of the INS and GPS sensor characteristics, called the artificial-intelligence-based segmented forward predictor. This method uses radial basis function neural networks to predict INS position and velocity errors during GPS outages, resulting in reliable performance. The performance of the proposed method is examined using real field test data of both navigational and tactical grade INS integrated with GPS. The results have shown that the proposed method outperforms KF, especially during long GPS outages.

Assessment of Dynamic Measurement Accuracy of GPS in Three Directions

Abstract: Global positioning system (GPS) technology is an emerging tool for measuring and monitoring both static and dynamic displacement responses of large civil engineering structures to gust winds. The accuracy of dynamic displacement measurement using GPS at a subcentimeter to millimeter level, however, depends on many factors such as data sampling rate, satellite coverage, atmospheric effect, multipath effect, and GPS data processing methods. This paper aims to assess the dynamic displacement measurement accuracy of GPS in three orthogonal directions for applications in civil engineering. For this purpose, a motion simulation table was first developed as a test station, simulating various types of 2D motions of either tall buildings in a horizontal plane or long-span bridges in a vertical plane. The antenna of a GPS receiver was then installed on the motion simulation table and was used to measure the table motion in an open area. A band-pass filtering scheme was finally designed and applied to the table motion data recorded by the GPS. The comparison of the table motion recorded by the GPS with the original motion generated by the table shows that the GPS can measure horizontal and vertical dynamic displacements accurately within a certain amplitude and frequency range. The test results also demonstrate that the GPS can trace wind-induced dynamic displacement responses measured from a tall building in the horizontal plane and a long-span bridge deck in the vertical plane satisfactorily.

Robust positioning technique in low-cost DR/GPS for land navigation

Abstract: This paper describes a dead-reckoning (DR) construction for land navigation and sigma-point-based receding-horizon Kalman finite-impulse response (SPRHKF) filter for DR/GPS integration system. A simple DR construction is adopted to improve the performance of both pure land DR navigation and DR/GPS integration system. In order to overcome the flaws of the extended Kalman filter (EKF), the sigma-point KF (SPKF) is merged with the receding-horizon strategy. This filter has several advantages over the EKF, the SPKF, and the RHKF filter. The advantages include the robustness to the system model uncertainty, the initial estimation error, temporary unknown bias, etc. The computational burden is reduced. Especially, the proposed filter works well even in the case of exiting the unmodeled random walk of the inertial sensors, which can occur in the microelectromechanical systems' inertial sensors by temperature variation. Therefore, the SPRHKF filter can provide the navigation information with good quality in the DR/GPS integration system for land navigation seamlessly

Experimental study on the estimation of lever arm in GPS/INS

Abstract: Lever-arm uncertainty can be an important error source in the integration of the Global Positioning System (GPS) and inertial navigation system (INS). This paper presents both numerical and experimental studies on the estimation of the lever arm in the integration of a very-low-grade inertial measurement unit (IMU) with an accurate single-antenna GPS measurement system. Covariance simulation results showed that maneuvers play an important role on the estimation of the lever arm and attitude. The length of the lever arm has a rather insignificant effect on the estimation of these. Experimental tests conducted with a low-cost microelectromechanical system (MEMS) IMU and a carrier-phase differential GPS (CDGPS) measurement system showed that the lever arm can be estimated with centimeter-level accuracy. The test results confirmed that angular motions and horizontal accelerations improve the estimates of the lever arm and yaw angle, respectively.

Global position system (GPS) user receiver and geometric surface processing for all-in-view coherent GPS signal PRN codes acquisition and navigation solution

Abstract: A method and system for enabling a more robust detection, acquisition and positioning solution capability for a GPS device. The system and method uses GPS satellite ranging signals based on a simultaneous, all-in-view coherent PRN code signal processing scheme, rather than acquisition of GPS signals one at a time, in order to predict a location of a GPS user receiver. Additionally, image processing techniques, ultra-tight coupling processing techniques, or a combination thereof, are used to further enhance accuracy in determining the location of the user receiver. Signal processing techniques are used to determine the location of the GPS user receiver when no GPS satellite ranging signals can be individually detected, or when only one or two strong GPS satellite ranging signals can be individually detected in weak signal environments, jamming conditions, and a combination thereof.

Lever Arm Compensation for GPS/INS/Odometer Integrated System

Abstract: For more accurate navigation, lever arm compensation is considered. The compensation method for GPS and an odometer is introduced and new compensation methods are proposed for an odometer to consider the effect of coordinate transformation errors and the scale factor error. The methods are applied to a GPS/INS/odometer integrated system and the simulation and experimental results show its effectiveness. Navigation is defined as all the related theories and technologies for obtaining position, velocity and attitude of a vehicle. With the use of navigation technology, one can know his/her position and can plan trajectory for their destination. Nowadays, especially, the need for the navigation of land vehicles has rapidly increased. In the near future, ubiquitous personal navigation will be spread and navigation will become a more essential technology. The Global Positioning System (GPS) is a satellite- based radio navigation system (1). It allows a user with a receiver to obtain accurate position information anywhere on the globe. It provides position information whose errors would not increase with respect to time. However, a signal from the GPS satellite cannot often arrive at a receiver in an urban area. In those cases, it cannot provide any position information.

Analysis of an Ultra-Tightly Coupled GPS/INS System in Jamming

Abstract: The performance of an Ultra-Tightly Coupled (UTC) Global Positioning System/Inertial Navigation System (GPS/INS) is evaluated using a system simulation of the GPS receiver and navigation processing. The UTC system being analyzed uses a bank of pre-filters to estimate code delay error and Doppler frequency error for each satellite. These outputs are sent to a central Kalman navigation filter. This central processor generates estimates of inertial navigation position, velocity, and attitude errors; IMU biases; and user clock errors, which are used to correct the navigation solution. In the UTC approach, outputs from the central navigation processor, after projection into satellite line-of-sight coordinates, are used to control the code and carrier replica signals for each satellite channel. In contrast, a conventional tightly coupled GPS/INS system uses separate tracking loops for each satellite channel, which operate autonomously. As a result, the UTC design is considered more robust to jamming and vehicle dynamics. Closed-loop UTC navigation performance is evaluated over a realistic precision guided munition (PGM) scenario in the presence of broadband jamming directed against the GPS system. A realistic IMU error model is assumed, and UTC performance is evaluated over a range of jamming levels. Some preliminary conclusions are then formed about the effectiveness of the UTC approach.

Fusion of Map and Sensor Data in a Modern Car Navigation System

Abstract: The main tasks of car navigation systems are positioning, routing, and guidance. This paper describes a novel, two-step approach to vehicle positioning founded on the appropriate combination of the in-car sensors, GPS signals, and a digital map. The first step is based on the application of a Kalman filter, which optimally updates the model of car movement based on the in-car odometer and gyroscope measurements, and the GPS signal. The second step further improves the position estimate by dynamically comparing the continuous vehicle trajectory obtained in the first step with the candidate trajectories on a digital map. This is in contrast with standard applications of the digital map where the current position estimate is simply projected on the digital map at every sampling instant.

Accuracy of high‐rate GPS for seismology

Abstract: We built a device for translating a GPS antenna on a positioning table to simulate the ground motions caused by an earthquake. The earthquake simulator is accurate to better than 0.1 mm in position, and provides the "ground truth" displacements for assessing the technique of high-rate GPS. We found that the root-mean-square error of the 1-Hz GPS position estimates over the 15-min duration of the simulated seismic event was 2.5 mm, with approximately 96% of the observations in error by less than 5 mm, and is independent of GPS antenna motion. The error spectrum of the GPS estimates is approximately flicker noise, with a 50% decorrelation time for the position error of approx.1.6 s. We that, for the particular event simulated, the spectrum of dependent error in the GPS measurements. surface deformations exceeds the GPS error spectrum within a finite band. More studies are required to determine whether a generally optimal bandwidth exists for a target group of seismic events.

A Performance Comparison of Tightly Coupled GPS/INS Navigation Systems based on Extended and Sigma Point Kalman Filters

Abstract: In tightly coupled GPS/INS integration, the data fusion algorithm is faced with nonlinear system dynamics and measurement models. The extended Kalman filter (EKF) approximates the propagation of Gaussian random vectors through these nonlinear equations using a linear transformation. This captures mean and covariance to first order accuracy only. Sigma-point Kalman filters (SPKF) offer third order accuracy. In this paper, the performance of EKF-based and SPKF-based tightly coupled GPS/INS systems is compared in numerical simulations. The simulation results were confirmed by post-processing raw GPS and inertial sensor data that was recorded during a test drive. It was found that, except for specific situations without practical relevance, EKF and SPKF offer an identical performance. This is due to the fact that for tightly coupled—as well as loosely coupled—GPS/INS integration, the higher-order transformation terms are negligible. This result was shown analytically.

Architecture and System Performance of SPAN -NovAtel's GPS/INS Solution

Abstract: As a GPS receiver manufacturer, NovAtel is in a unique position to build a GPS/INS navigation system. The Synchronized Position Attitude Navigation (SPAN) system is based on OEM4 receiver technology combined with an Inertial Measurement Unit (IMU). The IMU integration is tightly coupled with access to the GPS receiver core. The integrated system provides real time position, velocity and attitude. GPS outages can be seamlessly bridged, enabling more reliable navigation through challenging environments like urban canyons. Additionally, GPS performance is improved with the integration of inertial measurements, allowing for faster signal reacquisition and faster return to a fixed integer carrier phase solution after signal outage. The real time solution is computed on board the receiver and raw data can be simultaneously logged for post-processing. Post processing is performed by NovAtel’s Waypoint Inertial Explorer package. This paper discusses NovAtel's approach to INS/GPS system architecture. To demonstrate the performance of the SPAN system, data will be collected under real world conditions in a land vehicle. Test results will show system performance with various levels of GPS aiding and with wheel sensor aiding. The real time solution will be compared to the post-processed solution. Methods to deal with the constraints of real time will be discussed. The accuracy benefits of a post-processed solution will be demonstrated as well.

Time-Differenced Carrier Phase Measurements for Tightly Coupled GPS/INS Integration

Abstract: A tightly coupled GPS/INS system is characterized by the fact that pseudorange and deltarange measurements are processed in the navigation filter in order to estimate the errors of the inertial navigation solution and to calibrate the inertial measurement unit. In this paper, the usage of time differenced carrier phase measurements instead of the delta range measurements is proposed. Usually, DGPS corrections are required in order to exploit the high accuracy of the carrier phase measurements by removing the common mode errors like ionospheric errors, ephemeris errors, or satellite clock errors. Then, techniques like carrier aided smoothing or ambiguity fixing can be applied. With the approach described in this paper, DGPS corrections are not required. Additionally, a fixing of the integer ambiguities, which is especially difficult when a single frequency receiver is used, is not required either. Forming time differences of successive carrier phase measurements, the constant integer ambiguities and most of the slowly varying common mode errors are removed. These carrier phase differences do not allow for an absolute centimeter-level positioning as it can be achieved with a DGPS base station and an ambiguity fixing, but the noise in the position information is reduced and the accuracy of the velocity and attitude estimates are improved. Details of this approach are clarified and the processing of this type of measurement in the navigation filter is addressed. The improvement in performance is illustrated via hardware-in-the-loop test results and the analysis of flight test data collected with a micro aerial vehicle.

Low-cost Tightly Coupled GPS/INS Integration Based on a Nonlinear Kalman Filtering Design

Abstract: This paper describes the design of a tightly coupled GPS/INS integration system based on nonlinear Kalman filtering methods. The traditional methods include linearization of the system around a nominal trajectory, and the extended Kalman filtering (EKF) method which linearizes the system around the previous estimate, or the predication, whichever is available. The recently proposed sigma-point Kalman filtering (SPKF) method uses a set of weighted samples (sigma points) to completely capture the first and second order moments of the prior random variable. In contrast to the EKF, the SPKF has a simpler implementation as it does not require the Jacobian matrices – the computation of which may lead to analytical or computational problems in some applications. This research is conducted under the Australian Cooperative Research Centre (CRC) for Spatial Information (CRC-SI) project 1.3 'Integrated Positioning and Geo-referencing Platform'. The project aims to develop a generic hardware/software platform for positioning and imaging sensor integration. The current work focuses on development of software and algorithms, and a field programmable gate arrays (FPGA) based GPS/INS data logging system. In the current development phase, a tightly coupled GPS/INS integration system based on a linearization around the INS solution has been designed and implemented. The system uses the GPS pseudorange and Doppler measurements to estimate the INS errors. This paper describes further developments of the integration filter design based on the EKF and SPKF methodologies, in order to compare the performance of nonlinear filtering approaches. Experimental results are presented and further planned developments are outlined.

A combined algorithm of improving INS error modeling and sensor measurements for accurate INS/GPS navigation

Abstract: Although the integrated system of a differential global positioning system (DGPS) and an inertial navigation system (INS) had been widely used in many geodetic navigation applications, it has sometimes a major limitation. This limitation is associated with the frequent occurrence of DGPS outages caused by GPS signal blockages in certain situations (urban areas, high trees, tunnels, etc.). In the standard mechanization of INS/DGPS navigation, the DGPS is used for positioning while the INS is used for attitude determination. In case of GPS signal blockages, positioning is provided using the INS instead of the GPS until satellite signals are obtained again with sufficient accuracy. Since the INS has a very short-time accuracy, the accuracy of the provided INS navigation parameters during these periods decreases with time. However, the obtained accuracy in these cases is totally dependent on the INS error model and on the quality of the INS sensor data. Therefore, enhanced navigation parameters could be obtained during DGPS outages if better inertial error models are implemented and better quality inertial measurements are used. In this paper, it will be shown that better INS error models are obtained using autoregressive processes for modeling inertial sensor errors instead of Gauss–Markov processes that are implemented in most of the current inertial systems and, on the other hand, that the quality of inertial data is improved using wavelet multi-resolution techniques. The above two methods are discussed and then a combined algorithm of both techniques is applied. The performance of each method as well as of the combined algorithm is analyzed using land-vehicle INS/DGPS data with induced DGPS outage periods. In addition to the considerable navigation accuracy improvement obtained from each single method, the results showed that the combined algorithm is better than both methods by more than 30%.

An unassisted indoor gps receiver

Abstract: The present invention provides GPS receivers capable of tracking very weak GPS signals particularly in an indoor environment without assistance from an external server or a network. In a preferred embodiment, a GPS receiver initially acquires and locks onto GPS satellite signals to compute receiver position outdoors. The GPS receiver then tracks at least one satellite signal indoors to maintain acquisition parameters for quick acquisition of GPS signals. To save power, the receiver automatically goes to the sleep state and periodically wakes up, i.e., powers up, to maintain the at least one satellite signal tracking. During the wakeup state, the receiver collects ephemeris data from the at least one satellite signal when the ephemeris data needs to be updated for quick acquisition of GPS signals.

A low-cost attitude heading reference system by combination of GPS and magnetometers and MEMS inertial sensors for mobile applications

Abstract: This paper describes a prototype system for attitude and heading determination. A L1-only GPS receiver is integrated with microelectromechanical gyroscopes, accelerometers and magnetometers. In contrast to a multi-antenna/multi-receiver GPS attitude determination system, this system uses a single antenna/single receiver configuration to derive standalone velocity and acceleration solutions from the GPS L1 carrier phase measurements. No reference station is needed to form differences of carrier phase measurements for the velocity and acceleration calculation. The GPSderived acceleration is further used in the attitude determination by combination with the three-dimension acceleration sensed by the accelerometers. The magnetometers sense the Earth’s magnetic field intensity, and can give the heading estimation regardless of the status of the host platform. To satisfy real-time applications, infinite impulse response differentiators instead of finite impulse response differentiators are used to derive the acceleration from GPS. The algorithms have been implemented and their efficiency demonstrated by experiments.

Non-GPS Navigation for Emergency Responders

Abstract: - This paper introduces a novel navigation system for walking persons The system is of particular benefit for emergency responders, who often have to enter and move around in large structures where GPS is unavailable We refer to our system as “Personal Odometry System” (POS) The POS measures the position of a walking person relative to a known starting position, such as the entrance to a building This is accomplished by instrumenting one boot of the subject with a 3-axis gyroscope and a 3-axis accelerometer (collectively called “inertial measurement unit” – IMU) This paper describes the POS hardware and explains the basics of our approach The paper also presents extensive experimental results, which illustrate the utility and practicality of our system I I NTRODUCTION This paper describes our Personal Odometry System (POS) for measuring and tracking the momentary location and trajectory of a walking person, even if GPS is not available We believe that such a system might be of particular value for emergency responders For example, fire fighters entering a burning building are at risk to be injured and unable to report their position With the POS reporting the user’s position to a central command post, each emergency responder’s location could be tracked in real-time Another application involves the “clearing” of a large building by emergency or security personnel Their challenge often is to keep track of rooms already cleared and areas that were not cleared, yet Our system’s ability to track each person’s location provides a useful solution for this problem Our proposed POS does not require GPS This is an important distinction, since GPS is not available indoors Furthermore, GPS is unreliable under dense foliage, in so-called “urban canyons,” and generally in any environment, in which a clear view of a good part of the sky is not available There are some approaches to personal position estimation without GPS Typically, these systems require external references, also called “fiducials,” such as preinstalled active beacons, receivers, or optical retroreflectors Common to all fiducial-based position estimation systems is that the fiducials must be installed in the work space at precisely surveyed locations before the system can be used This installation is time consuming and expensive, and in case of emergency response completely unfeasible Fiducial-based systems also require an active radiation source, such as infrared light [1], ultrasound [2], or magnetic fields [3], which may be undesirable in security-related applications Generally, fiducial-based systems perform well and are able to provide absolute position and orientation in real-time If the application permits the installation of fiducials ahead of time, then these systems have the significant advantage that errors don’t grow with time, as is the case in our POS Another way of implementing absolute position estimation is computer vision ([4] and [5]) Images are compared and matched against a pre-compiled database Computer vision has the advantage that the environment does not need to be modified, but the approach requires potentially very large databases Work is also being done on so-called Simultaneous Location and Mapping (SLAM) methods, which don’t require a precompiled database However, SLAM systems are not as reliable, may accrue errors over time and distance, and poor visibility and unfavorable light conditions can result in completely false position estimation [6][7] The scientific literature offers only very few approaches that do not require external references The simplest one of them is the pedometer, that is, a device that counts steps Pedometers must be calibrated for the stride length of the user and they produce large errors when the user moves in any other way than his or her normal walking pattern One commercially available personal navigation system based on this principle is the Dead Reckoning Module (DRM) by PointResearch [8] It uses accelerometers to identify steps, and linear displacement is computed assuming that the step size is constant Orientation is measured using a digital compass, which is combined with the traveled distance (step counts) to estimate 2-D position The performance of this system depends on the accuracy of determining the stride

Integration of a GPS aided Strapdown Inertial Navigation System for Land Vehicles

Abstract: The estimation accuracy of a low-cost inertial navigation system (INS) is limited by the accuracy of the used sensors and the imperfect mathematical modeling of the error sources. By fusing the INS data with GPS data, the errors can be bounded and the accuracy increases considerably. In this project, a low-cost in-house constructed inertial measurement unit (IMU) and an off-the-shelf GPS receiver are used for the data acquisition. The measurements are integrated with a loosely coupled GPS aided INS approach. For the assessment of the results, one data set with real data obtained from a field test is available. The tuning of the covariance matrices is a delicate adjustment and does not always provide convergence. Values for acceptable results could be found and two implementations of inertial navigation systems are compared. The use of nonholonomic constraints showed a dramatic increase in the accuracy. An analysis of the importance and influence of different IMU sensor errors provides a foundation for the modeling and inclusion of further error states in the extended Kalman filter.

GPS gyro calibration

Abstract: GPS gyro calibration methods and systems are described. In an embodiment, a ground station can receive antenna position data for a spot beam antenna from a global positioning system (GPS) platform where the antenna position data indicates a boresight direction of the spot beam antenna. GPS-enabled receiver(s) can receive scan signals transmitted via the spot beam antenna of the GPS platform, and the GPS-enabled receivers can determine signal power measurements for each of the scan signals. The ground station can receive the signal power measurements from the GPS-enabled receiver(s) and estimate a pointing error of the spot beam antenna based on the signal power measurements and the antenna position data received from the GPS platform. The ground station can then determine gyro calibration parameters from the estimated pointing error and communicate the gyro calibration parameters to the GPS platform to calibrate for gyro drift errors.

Development of Precise GPS/INS/Wheel Speed Sensor/Yaw Rate Sensor Integrated Vehicular Positioning System

Abstract: This paper aims to develop a more precise vehicular positioning system during GPS outages by integrating GPS, a tactical grade HG1700 IMU, as well as Wheel Speed Sensor and a Yaw Rate Sensor. Using a tight coupling strategy, three types of sensor integration schemes are proposed, namely GPS/INS/Wheel Speed Sensor, GPS/INS/Yaw Rate Sensor and GPS/INS/Yaw Rate Sensor/Wheel Speed Sensor. The models for each of the schemes are discussed in detail including the sensor error models. The benefits after integrating the Wheel Speed Sensor and the Yaw Rate Sensor are investigated in terms of positioning accuracy during GPS data outages. Furthermore, the reduction in the time to fix the carrier phase ambiguities after various GPS outage durations is analyzed.

Systems and methods for augmenting an inertial navigation system

Abstract: Systems and methods for augmenting an inertial navigation system (INS) include outputting from the INS position information associated with the implement and adjusting the implement based upon a comparison of the position information of the implement and a desired position of the implement. The INS is periodically re-initialized using error estimates generated by a kalman filter as a function of position information from one or more positioning (or measuring) devices, such as a fan laser, an automatic total station (ATS), a GNSS receiver, or a ground based radio positioning system, to correct a drift of the position information that may be caused by inherent characteristics of the INS.