Showing papers presented at "IEEE/ION Position, Location and Navigation Symposium in 2008"

Indoor PDR performance enhancement using minimal map information and particle filters

Abstract: For professional users such as firefighters and other first responders, GNSS positioning technology (GPS, assisted GPS) can satisfy outdoor positioning requirements in many instances. However, there is still a need for high-performance deep indoor positioning for use by these same professional users. This need has already been clearly expressed by various communities of end users in the context of WearIT@Work, an R&D project funded by the European Community's Sixth Framework Program. It is known that map matching can help for indoor pedestrian navigation. In most previous research, it was assumed that detailed building plans are available. However, in many emergency / rescue scenarios, only very limited building plan information may be at hand. For example a building outline might be obtained from aerial photographs or cataster databases. Alternatively, an escape plan posted at the entrances to many building would yield only approximate exit door and stairwell locations as well as hallway and room orientation. What is not known is how much map information is really required for a USAR mission and how much each level of map detail might help to improve positioning accuracy. Obviously, the geometry of the building and the course through will be factors consider. The purpose of this paper is to show how a previously published Backtracking Particle Filter (BPF) can be combined with different levels of building plan detail to improve PDR performance. A new in/out scenario that might be typical of a reconnaissance mission during a fire in a two-story office building was evaluated. Using only external wall information, the new scenario yields positioning performance (2.56 m mean 2D error) that is greatly superior to the PDR-only, no map base case (7.74 m mean 2D error). This result has a substantial practical significance since this level of building plan detail could be quickly and easily generated in many emergency instances. The technique could be used to mitigate heading errors that result from exposing the IMU to extreme operating conditions. It is hoped that this mitigating effect will also occur for more irregular paths and in larger traversed spaces such as parking garages and warehouses.

Cascaded estimation architecture for integration of foot-mounted inertial sensors

Abstract: An algorithm for integrating foot-mounted inertial sensor platforms is presented. The proposed integration scheme is based on a cascaded estimation architecture. A lower Kalman filter is used to estimate the step-wise change of position and direction of one or optionally both feet respectively. These estimates are used in turn as measurements in an upper particle filter, which is able to incorporate nonlinear map-matching techniques. To ease the integration of both feet a simple mechanical pedestrian model is developed. The proposed algorithm is verified using computer simulations and experimental data.

Tight coupling of GPS, laser scanner, and inertial measurements for navigation in urban environments

Abstract: Many applications can be envisioned for accurate, robust, and reliable navigation solution in challenging urban environments. Examples of existing and prospective applications include, but are not limited to, navigation, guidance, and control of autonomous vehicles (including both ground and aerial vehicles) for urban surveillance and reconnaissance; collection of geographical information system (GIS) data in cities; monitoring of urban infrastructure for situational awareness; and, precise automotive applications such as automated lane keeping. If used by themselves, none of the existing navigation technologies have the potential to fully satisfy the requirements for reliable and accurate navigation in urban environments. Hence, this paper develops a multi-sensor integrated solution that combines the complementary features of the Global Positioning System (GPS), laser scanner feature-based navigation, and inertial navigation for urban scenarios. GPS and laser scanner-based navigation ideally complement each other for urban navigation. The laser scanner-based navigation relies on the availability of structures (lines and surfaces) within the scan range (80 m, typically). Features (such as lines) are first extracted from laser scan images and then used for position and attitude determination. In urban areas, if there exists a building wall that blocks GPS signals, this wall creates a feature in the laser scan image. On the other hand, for open streets with limited features, the GPS signal is generally unobstructed. Thus, GPS and laser data can be combined into integrated solution architecture. The system architecture developed also exploits INS navigation states for improved solution robustness: e.g., for robust feature association between scan images and for coasting through instances where sufficient number of combined GPS/laser measurements is unavailable. A tightly coupled GPS/laser scanner/INS mechanization is developed and applied for centimeter- accurate trajectory reconstruction. The paper uses live urban data to demonstrate that combined GPS and laser scanner data generally support the observability of navigation states at any part of the urban trajectory; and, for those limited cases where insufficient GPS/laser measurements are available, the INS coasting option can be efficiently utilized. Test results presented also show that the developed tightly coupled GPS/laser scanner/INS solution provides accurate trajectory reconstruction capabilities (one sigma error residuals are at a cm-level) in challenging urban environments.

Coarse alignment for marine SINS using gravity in the inertial frame as a reference

Abstract: Marine strapdown inertial navigation systems (SINS) inevitably experience disturbing motion, even if the carrier ship is moored. The method of ground coarse alignment, which is based on the assumption that SINS is on a stationary carrier with limited vibration, therefore cannot be used to perform the marine SINS coarse alignment. In this paper, a novel method using the gravity in the inertial frame as a reference is investigated for marine SINS alignment. Its algorithmic principle is described in details. The results obtained from both simulation and turntable-test data show that the attitude determined by this novel method can meet the accuracy requirement of coarse alignment and it can be used as input for fine alignment.

An integrated reduced inertial sensor system — RISS / GPS for land vehicle

Abstract: This paper demonstrates a low cost navigation solution that can efficiently work, in real-time, in denied GPS environment. It explores a reduced inertial sensor system (RISS) involving single-axis gyroscope and two-axis accelerometers together with a speed sensor to provide full navigation solution in denied GPS environments. With the assumption that the vehicle mostly stay in the horizontal plane, the vehicle speed obtained from the speed sensor are used together with the heading information obtained from the gyroscope to determine the velocities along the East and North directions. Consequently, the vehiclespsila longitude and latitude are determined. The position and velocity errors are estimated by Kalman filter (KF) relying on RISS dynamic error model and GPS position and velocity updates. The two accelerometers pointing towards the forward and transverse directions are used together with a reliable gravity model to determine the pitch and roll angles. This paper analyzes and discusses the merits and limitations of the proposed RISS system and its integration with GPS. The performance of the proposed method is examined by conducting road test experiment in a land vehicle.

Gnss performance enhancement in urban environment based on pseudo-range error model

Abstract: Today, GNSS (Global Navigation Satellite System) systems made their entrance in the transport field through applications such as monitoring of containers or fleet management. These applications do not necessarily request a high availability, integrity and accuracy of the positioning system. For safety applications (for instance management of level crossing), the performances require to be more stringent. Moreover all these transport applications are used in dense urban or sub-urban areas, resulting in signal propagation variations. This increases difficulty of getting the best reception conditions for each available satellite signal. The consequences of environmental obstructions are unavailability of the service and multipath reception that degrades in particular the accuracy of the positioning. Our works consist in two main tasks. The first one concerns the pseudo-range error model. Indeed, the model differs in relation of the satellite state of reception. When the state of reception is direct, as described in literature, the associated pseudo-range error model is a Gaussian distribution. However, when the state of reception is NLOS (Non Line Of Sight), this assumption is no more valid. We have shown that the associated model can be approximated by a Gaussian mixture. The Second contribution concerns the reception state evolution. We have modeled the propagation channel with a Markov chain. From the state of reception of each satellite, we deduce the appropriated error model. This model is then used in a filtering process to estimate the position. The approach is based on filtering methodology and on the application of a Jump Markov System algorithm.

Redundant MEMS-IMU integrated with GPS for performance assessment in sports

Abstract: In this article, we investigate two different algorithms for the integration of GPS with redundant MEMS-IMUs. Firstly, the inertial measurements are combined in the observation space to generate a synthetic set of data which is then integrated with GPS by the standard algorithms. In the second approach, the method of strapdown navigation needs to be adapted in order to account for the redundant measurements. Both methods are evaluated in experiments where redundant MEMS-IMUs are fixed in different geometries: orthogonally-redundant and skew-redundant IMUs. For the latter configuration, the performance improvement using a synthetic IMU is shown to be 30% on the average. The extended mechanization approach provides slightly better results (about 45% improvement) as the systematic errors of the individual sensors are considered separately rather than their fusion when forming compound measurements. The maximum errors are shown to be reduced even by a factor of 2.

The soft iron and hard iron calibration method using extended kalman filter for attitude and heading reference system

Abstract: The calibration method of the soft iron and hard iron distortion based on attitude and heading reference system (AHRS) can boil down to the estimation of 12 parameters of magnetic deviation, normally using 12-state Kalman filter (KF) algorithm. The performance of compensation is limited by the accuracy of local inclination angle of magnetic field and initial heading. A 14-state extended Kalman filter (EKF) algorithm is developed to calibrate magnetic deviation, local magnetic inclination angle error and initial heading error all together. The calibration procedure is to change the attitude of AHRS and rotate it two cycles. As the strapdown matrix can hold high precision after initial alignment of AHRS in short time for the gyropsilas short-term precision, the magnetic field vector can be projected onto the body frame of AHRS. The experiment results demonstrate that 14-state EKF outperforms 12-state KF, with measurement errors exist in the initial heading and local inclination angle. The heading accuracy (variance) after compensation is 0.4 degree for tilt angle ranging between 0 and 60 degree.

MEMS IMU for AHRS applications

Abstract: Northrop Grumman, LITEF is developing MEMS (micro-electro-mechanical systems) based Inertial Measurement Units (IMU) for future attitude and heading reference systems (AHRS) with a target accuracy of 5 deg/h for the gyroscopes and 2.5 mg for the accelerometers. Within the technology development phase, prototype single axis gyroscopes have been realized and extensively tested for effects including temperature, acoustic and vibration sensitivities. These devices employ micro-machined all-silicon gyroscope sensor chips processed with deep reactive ion etching (DRIE). Silicon fusion bonding ensures pressures smaller than 3middot10-2 mbar. Sophisticated analog electronics and digital signal processing condition the capacitive pick-off signals and realize full closed loop operation. The current results with overall bias error smaller than 2 deg/h to 5 deg/h, scale factor error 1000 deg/s and angular random walk <0.4 radic/vh indicate that stable production of 5 deg/h gyroscopes is realistic. The fabrication technology for capacitive, pendulous accelerometer chips is based on that used for the gyros with only an increase in the enclosed pressure to obtain overcritical damping. Pulse width modulation (PWM) within a digital control loop is used to realize closed loop operation. Accelerometer chips have been tested over temperature with a residual bias error <2.0 mg and a scale factor error <1400 ppm. These sensor chips have been integrated into an IMU whereby the power budget and size of the sensor electronics have been optimized. In this paper the salient features of the gyro and accelerometer designs are presented together with an overview of the IMU system architecture. Measurement results, with a focus on environmental characteristics and robustness, are included.

Wi-Fi based indoor localization and tracking using sigma-point Kalman filtering methods

Abstract: Estimating the location of people and tracking them in an indoor environment poses a fundamental challenge in ubiquitous computing. The accuracy of explicit positioning sensors such as GPS is often limited for indoor environments. In this study, we evaluate the feasibility of building an indoor location tracking system that is cost effective for large scale deployments, can operate over existing Wi-Fi networks, and can provide flexibility to accommodate new sensor observations as they become available. At the core of our system is a novel location and tracking algorithm using a sigma-point Kalman smoother (SPKS) based Bayesian inference approach. The proposed SPKS fuses a predictive model of human walking with a number of low-cost sensors to track 2D position and velocity. Available sensors include Wi-Fi received signal strength indication (RSSI), binary infrared (IR) motion sensors, and binary foot-switches. Wi-Fi signal strength is measured using a receiver tag developed by Ekahau Inc. The performance of the proposed algorithm is compared with a commercially available positioning engine, also developed by Ekahau Inc. The superior accuracy of our approach over a number of trials is demonstrated.

Modeling and bounding low cost inertial sensor errors

Abstract: This paper presents a methodology for developing models for the post-calibration residual errors of inexpensive inertial sensors in the class normally referred to as ldquoautomotiverdquo or ldquoconsumerrdquo grade. These sensors are increasingly being used in real-time vehicle navigation and guidance systems. However, manufacturer supplied specification sheets for these sensors seldom provide enough detail to allow constructing the type of error models required for analyzing the performance or assessing the risk associated with navigation and guidance systems. A methodology for generating error models that are accurate and usable in navigation and guidance systemspsila sensor fusion and risk analysis algorithms is developed and validated. Use of the error models is demonstrated by a simulation in which the performance of an automotive navigation and guidance system is analyzed.

Differential barometry in personal navigation

Abstract: In many personal navigation applications accurate altitude information is required. Finding a correct floor in a tall building or precise guidance in multi-layer intersection is not possible with two-dimensional navigation system. Satellite navigation systems provide altitude information, but accuracy is not necessarily sufficient for this kind of situations. Barometers can be used to improve the accuracy and availability of the altitude solution. The objective of this study was to find relevant error sources of barometer based altitude in the context of personal navigation. MEMS barometer data were collected in several scenarios where different disturbances affect the pressure reading. To separate error sources, reference barometer at known altitude was used. The results show that barometers in differential mode provide highly accurate altitude solution, but local disturbances in pressure need to be taken into account in the application design.

Quaternion attitude estimation for miniature air vehicles using a multiplicative extended Kalman filter

Abstract: Utilizing the Euler-Rodrigues symmetric parameters (attitude quaternion) to describe vehicle orientation, we develop a multiplicative, nonlinear variation of the Kalman filter to fuse data from low-cost sensors. The sensor suite is comprised of gyroscopes, accelerometers, and a GPS receiver. Our filter states consist of the three components of an Euler attitude error vector. In parallel with the state time update, we utilize the gyroscope measurements for the time propagation of the attitude quaternion. The accelerometer and the GPS sensors are used independently for the measurement update portion of the filter. For both sensors, a vector arithmetic approach is used to determine the Euler attitude error vector. Following each measurement update, a multiplicative reset operation moves the attitude error information from the state into the attitude estimate. This reset operation utilizes quaternion algebra to implicitly maintain the unity-norm constraint. We demonstrate the effectiveness of our attitude estimation algorithm through flight simulations of aggressive maneuvers such as loops and small-radius circles.

Integrity in urban and road environments and its use in liability critical applications

Abstract: The use of integrity in the field of GNSS is usually linked to safety critical applications. This paper introduces the use of integrity in the so called liability critical applications i.e. those where undetected GNSS large position errors can generate significant legal or economic negative consequences. Unlike in civil aviation, liability critical applications are usually associated to an urban or road environment where position integrity becomes a real challenge basically derived from the effects to non-line of sight multipath. Electronic toll collection has been selected as a good example of liability critical applications and their requirements, and for analyzing how the use of integrity improves their performance. The paper focuses in a novel technique for the computation of positioning integrity in the identified environments, the so called isotropy-based protection levels, that is also believed to be a very promising technique for its application for safety critical applications and, thus, a potential contribution to the USA GNSS evolutionary architecture study (GEAS) and the EU GNSS Evolution Programme.

Compact, low-power chip-scale atomic clock

Abstract: We have successfully demonstrated a compact atomic frequency standard, the Chip-Scale Atomic Clock (CSAC), which achieves aggressive reductions in size and power while preserving good short-term stability. The device, based on Coherent Population Trapping (CPT), achieved volume less than 1 cm3, power consumption below 30 mW, and an Allan Deviation less than 1 times 10-11 (1 hour). This device incorporated a novel dual-pass reflective optical configuration based on a microstructured dual focus optic. Compact, low-power control electronics were developed based on an injection-locked voltage controlled oscillator (VCO) circuit. This approach enabled the combined power consumption of the VCO and microcontroller-based control electronics to be kept below 15 mW.

Enhancement of global vehicle localization using navigable road maps and dead-reckoning

Abstract: This paper presents a data fusion strategy for the global localization of car-like vehicles. The system uses raw GNSS measurements, dead-reckoning sensors and road map data. We present a new method to use the map information as a heading observation in a Kalman filter. Experimental results show the benefit of such a method when the GPS information is not available. Then, we propose a conservative localization strategy that relies mainly on dead-reckoned navigation. The GNSS measurements and the map information are not used when consistency tests are doubtful. Experimental tests indicate that the performance is effectively better when using only the available consistent information.

A set of high accuracy low cost metallic resonator CVG

Abstract: A set of all-digital metallic cylindrical CVGs of different diameters are presented in this paper. Innalabs CVG43 with resonator diameter of 43 mm, having natural frequency in the range 3 kHz and made of low damping and temperature stable material, is placed under vacuum cap with residual pressure of about 5 times 10-4 arm. The resonator Q factors reach values of 20000 - 30000 depending on resonator design and material used. CVG43 bias instability is about 0.03 deg/hr at stable temperature and about 0.5 deg/hr through its full temperature range (using temperature ramp of 1degC/min). Innalabs CVG25, which uses a 25 mm resonator diameter, has a bias instability of about 0.15-0.5 deg/hr, and a natural frequency approaching 6 kHz; is presented in Allan variance graphs at constant temperature and throughout its operating temperature range. Innalabs CVG17 gyro based on 17 mm resonator diameter has a bias instability of about 2.5 deg/hr and can survive many thousands of g's shock. This gyro is presented in Allan variance graphs and photos. This gyro sensor weighs about 20 grams and is ideal for unmanned aerial and underwater vehicle applications. Gyro accuracy through a wide temperature range is discussed and test results are presented. Three-axis units based on all types of these gyros are presented, as well. Future opportunities of each of these gyros are discussed.

Noise analysis for X-ray navigation systems

Abstract: Much as the Global Positioning System has ushered in an era of autonomous navigation on a global scale, X-ray navigation (XNAV) offers the possibility of autonomous navigation anywhere in the solar system. X-ray astronomers have identified a number of X-ray pulsars whose pulsed emissions have stabilities comparable to atomic clocks. X-ray navigation uses phase measurements from these sources to establish autonomously the position of the detector, and thus the spacecraft, relative to the solar system barycenter. This paper describes the development of a general noise model for X-ray navigation instruments. Key noise terms are identified and simple analytic expressions provided for each. This noise model is used to predict the performance of a typical XNAV system that could be used as the primary navigation resource on missions, including those beyond the orbit of Jupiter.

Acquisition of weak GNSS signals using a new block averaging pre-processing

Abstract: In this paper, we introduce a new approach for the acquisition of weak GNSS signals. For the GPS L1 signal, we utilize the replication property of the C/A code within each data bit to introduce a block averaging pre-processing (BAP) approach for improving receiver robustness against undesired signals. A large number of weighted signal blocks is coherently accumulated and synchronously averaged to obtain a single block with improved signal power. We present several properties of the proposed GNSS signals enhancement technique and we analyze its robustness against noise and different classes of interferers. Thus, we develop a software defined acquisition procedure using the efficient FFT correlation approach. We propose two acquisition algorithms based on the BAP approach. The first scheme implements the parallel code phase search in finding the 2-D spectrum peak using circular cross-correlations. In the second scheme, we exploit the BAP for a fast acquisition performing the frequency estimation prior to the 1-D code-phase search.

Low-cost MEMS sensor-based attitude determination system by integration of magnetometers and GPS: A real-data test and performance evaluation

Abstract: Attitude determination systems utilizing low cost MEMS sensors are increasingly becoming important due to its advantages in terms of the quickly improved precision, robust, high dynamic response and more significantly inexpensive costs of development and usage. However the large noises inherent in low cost MEMS sensors degrade the derived attitude precision if utilized through the conventional methods, e.g. initial alignment, strapdown inertial navigation mechanization. Therefore the novel application approach suitable for MEMS needs to be investigated. This paper describes an attitude determination system that is based on low cost MEMS inertial sensor, a triad of magnetometers and a commercial GPS receiver. Two main issues are addressed in the paper; firstly determination of the attitude initials, the algorithm is based on a quaternion formulation, a representative of attitude, of Wahbapsilas problem, whereby the error quaternion becomes the estimated state and is corrected by two observations of the earth magnetic field and gravity respectively. After the estimates converge, the derived attitude parameters are employed to initialize the inertial navigation calculations. Due to the large noises in MEMS sensor, there is a demand for external velocity and/or position corrections in the MEMS navigation calculations when system experiences translational motions. Hence secondly, GPS solutions are integrated in a Kalman filter by providing external velocity and position observations. A Kalman dynamic model is designed appropriate for MEMS sensor noise characteristics. The bias and drift are estimated by the integrated Kalman filter, which enables the online calibrations of MEMS sensor. The proposed approach has been developed and its efficiency is demonstrated by various experimental scenarios with real MEMS data and they are compared with Novatel SPAN-IMU reference.

Accurate signal strength prediction based positioning for indoor WLAN systems

Abstract: With development of IEEE802.11 based wireless local area networks (WLAN) there are several techniques to provide an accurate estimation of the location of mobile devices in indoor environment were presented. As the only available information at receiver side is the received signal strength indication (RSSI) from each WLAN access points (AP), technique called RSSI fingerprinting was proposed [1]. However one of the main drawbacks of RSSI based location is the extensive calibration phase to build a signal fingerprint.

Feasibility of Gauss-Newton method for indoor positioning

Abstract: This paper addresses the feasibility of using iterative least-squares (ILS) methods for indoor positioning, where coordinates are to be determined based on estimated/measured ranges. Special attention is given to the Gauss-Newton method, since it is well suited for solving (small residual) non-linear problems and most commonly applied in positioning. Dealing with non-linear inverse problems, the parameter estimation possibly features local minima next to the sought for global one, and the position estimator is inherently biased. In satellite positioning systems, e.g. GPS, or other large scale systems, an initial guess that leads the iterative method to a global convergence is not hard to obtain, and the bias due to non-linearity is negligible. However, in indoor systems, both effects can become problematic, and therefore extra care needs to be taken to properly apply the ILS methods. Two schemes are proposed in this paper, one to obtain a good initial guess and the other to test the significance of the bias due to non-linearity. The validation of the proposed schemes is supported by simulations as well as by experimental results obtained with an UWB acoustic positioning system, which achieves centimeter level positioning accuracy with LoS propagation and full bandwidth between 3.6 and 12.1 kHz (with equal wavelength compared to the radio signals with the bandwidth between 3.1 to 10.6 GHz allowed for UWB radio communications). The proposed schemes are validated with a number of system setups, differing in the positions of transmitters, the position of the receiver, redundancy, the bandwidth used and therefore the range measurement error.

System and algorithms for accurate indoor tracking using low-cost hardware

Abstract: In this paper we present a novel radio location system for indoor tracking and navigation. The system has been designed for applications such as emergency first responders where high accuracy is required, all nodes have only wireless connections, and the system must be able to be rapidly deployed. The application requirements are best satisfied using time-of-arrival based radio location, however the challenge is to do this at low cost. Specific issues addressed by the system include achieving frequency and time synchronization using low cost oscillators in each node and overcoming the variable propagation delay in the analog electronics from the use of low cost radio components, while operating in an environment characterized by strong multipath interference. Our approach has been to use low cost highly integrated electronic components and to use sophisticated signal processing to compensate for the limitations in the radio electronics. The system has been implemented and we demonstrate a median error of 0.15 m outdoors and 0.49 m in an indoor office environment with measurements performed through multiple walls.

A new approach for calculating position domain integrity risk for cycle resolution in carrier phase navigation systems

Abstract: This paper describes a new theoretical approach to quantify the position-domain integrity risk for cycle ambiguity resolution problems. It is typically conservatively assumed that all incorrectly fixed cycle ambiguities cause hazardously large position errors. Although practical and previously used, this conservative assumption can unnecessarily limit navigation availability for applications with stringent requirements for accuracy and integrity. In response, a new method for calculating the fault free integrity risk for carrier phase navigation algorithms is developed. In this method we evaluate the impact of incorrect fixes in the position domain. The method is used to define tight upper bounds on integrity risk in carrier phase navigation systems that demand high availability. A mechanism to implement this method with partially-fixed cycle ambiguity vectors is also derived. The improvement in navigation availability using this method is quantified through covariance analysis simulated over a range of error model parameters.

Post-correlation semi-coherent integration for high-dynamic and weak GPS signal acquisition

Abstract: Acquisition and ultimate tracking of a weak GPS signal faces several technical challenges, notably, possible data bit sign reversal every 20 ms and tolerable frequency error inversely proportional to the integration interval. Brute force search over all possible combinations of the unknown values is computationally prohibitive. Assisted GPS relying on external infrastructure for timing, data bit, and frequency error information is costly. Coherent techniques such as the block accumulating coherent integration over extended interval (BACIX) have recently been proposed to increase coherent integration. Although efficient, such coherent methods may still be too expensive except for high-end receivers and may not maintain the SNR performance when there are large frequency changes over the extended integration interval. In this paper, we set forth a novel method that utilizes the semi-coherent scheme for post-correlation integration. It is named as block accumulating semi-coherent integration of correlations (BASIC) and can be viewed as an extension of the BACIX algorithm. Although less sensitive than coherent integration, semi-coherent integration based on inter-block conjugate products is computationally more efficient. In addition, it can handle large frequency changes. The BASIC algorithm is first formulated in the paper. Computer simulation results are then presented to illustrate the operation and performance of the BASIC algorithm for joint estimation of the initial frequency, chirping rate (rate of change in frequency), bit sync, and bit sign pattern.

Gun hard inertial measurement unit based on MEMS capacitive accelerometer and rate sensor

Abstract: Smart munitions and missiles are increasingly incorporating inertial measurement units for guidance of short range weapon systems. In addition to usual high performance of the required sensors, namely, accelerometers and gyros, this application requires high shock survivability and post shock stability of the sensors. Colibrys has successfully developed a gun hard version of its accelerometer product and AIS has integrated these acceleration sensors and rate gyro to a gun hard IMU. The IMU has been extensively tested and characterized over the full temperature range, at Aerobutt and in many live shooting trials. The extreme shock performance of the IMU has been maintained by making the accelerometer shock resistant. This has been achieved by placing a specially designed mechanical stopper over the sensing element to protect the sensor from extreme shock levels by limiting the mechanical displacement of the MEMS element. This approach has resulted in excellent post shock performance of the acceleration sensor. Beyond this a special assembly technology has been developed at AIS to ensure that key shock components are filtered out and their energy is not transferred into the sensing element; and the vibrating elements are not affected by the components of the firing shock.

Tightly-coupled GPS / INS system design for autonomous urban navigation

Abstract: This paper analyzes the design decisions made in building the tightly-coupled position, velocity, and attitude estimator used as a position feedback signal for autonomous navigation in Cornell University's 2007 DARPA urban challenge robot, 'Skynet.' A statistical sensitivity analysis is conducted on Skynet's estimator by examining the changes in its output as critical design decisions are reversed. The effects of five design decisions are considered: map aiding via computer vision algorithms, inclusion of differential corrections, filter integrity monitoring, WAAS augmentation, and inclusion of carrier phases. The effects of extensive signal blackouts are also considered. All estimator variants are scrutinized both in a statistical sense and in a practical sense, by comparing each variant's performance on logged data recorded at the 2007 DARPA urban challenge.

Utilizing multipath reflections in deeply integrated GPS/INS architecture for navigation in urban environments

Abstract: This paper investigates the constructive use of multipath reflections of Global Positioning System (GPS) signals for navigation in urban environments. Urban navigation applications are generally characterized by a significant presence of multipath signals. In order to maintain reliable and accurate navigation capabilities, it is critical to distinguish between direct signal and multipath. At the same time, multipath reflections can be exploited as additional measurements for those cases where the number of direct path satellites is insufficient to compute the navigation solution. The paper develops a method for the identification of multipath reflections in received satellite signals: i.e. multipath is separated from direct signal and a line-of-site between the GPS receiver and a multipath reflecting object is determined. Once multipath reflections are identified, they can be used constructively for navigation. The method presented in the paper exploits an open loop batch-processing GPS receiver, laser scanner and inertial navigation system (INS) to identify multipath reflections in received satellite signals. Experimental GPS, inertial and laser scanner data collected in real urban environments are applied to demonstrate identification of multipath reflections.

Robust and efficient terrain navigation of underwater vehicles

Abstract: For terrain navigation to be a serious navigation tool in underwater navigation it must be robust and work well in flat bottomed areas. Furthermore it should be easy to incorporate with the vehicle's inertial navigation system (INS) so a bound can be placed on the system's position error. This paper describes the terrain navigation system developed for the Swedish Defence Materiel Administration's autonomous vehicles AUV62F and Sapphires. Both vehicles are battery powered and torpedo shaped with a diameter of 21". From the outset, the terrain navigation system was designed to work in flat bottomed areas; it uses many simultaneous sonar beams (400+) to measure the bottom topography, producing a unique underwater map position for the vehicle. When terrain navigating in flat bottomed areas, bottom topography measurement often gives many possible vehicle positions, i.e., the probability density function of the vehicle position is multimodal, so efficient and robust nonlinear Kalman filtering must be used. The terrain navigation module uses an optimal nonlinear Kalman filter called the FD filter. The FD filter numerically solves the stochastic differential equation that guides the vehicle positioning. The measurement updating is Bayesian. The filtering procedure is characterized by robustness, simplicity, and accuracy. It is also simple to incorporate independent measurements other than the terrain topography into the filter.

Comparison of low-cost GPS/INS sensors for Autonomous Vehicle applications

Abstract: Autonomous Vehicle applications (Unmanned Ground Vehicles, Micro-Air Vehicles, UAVpsilas, and Marine Surface Vehicles) all require accurate position and attitude to be effective. Commercial units range in both cost and accuracy, as well as power, size, and weight. With the advent of low-cost blended GPS/INS solutions, several new options are available to accomplish the positioning task. In this work, we experimentally compare three commercially available, off-the-shelf units insitu, in terms of both position, and attitude. The compared units are a Microbotics MIDG-II, a Tokimec VSAS-2GM, along with a KVH Fiber Optic Gyro. The position truth measure is from a Trimble Ag122 DGPS receiver, and the attitude truth is from the KVH in yaw. Care is taken to make sure that all measurements are taken simultaneously, and that the sensors are all mounted rigidly to the vehicle chassis. A series of measurement trials are performed, including light driving on coastal roads and highway speeds, static bench testing, and flight data taken in a light aircraft both flying up the coast as well as aggressively maneuvering. Allan Variance analysis performed on all of the sensors, and their noise characteristics are compared directly. A table is included with the final consistent models for these sensors, and a methodology for creating such models for any additional sensors as they are made available. The Microbotics MIDG-II demonstrates performance that is superior to the Tokimec VSAS-2GM, both in terms of raw positioning data, as well as attitude data. While both perform quite well during flight, the MIDG is much better during driving tests. This is due to the MIDG internal tightly-coupled architecture, which is able to better fuse the GPS information with the noisy inertial sensor measurements.