This paper presents a novel methodology that estimates position and orientation using one position sensor and one inertial measurement unit. The proposed method estimates orientation using a particle filter and estimates position and velocity using a Kalman filter (KF). In addition, an expert system is used to correct the angular velocity measurement errors. The experimental results show that the orientation errors using the proposed method are significantly reduced compared to the orientation errors obtained from an extended Kalman filter (EKF) approach. The improved orientation estimation using the proposed method leads to better position estimation accuracy. This paper studies the effects of the number of particles of the proposed filter and position sensor noise on the orientation accuracy. Furthermore, the experimental results show that the orientation of the proposed method converges to the correct orientation even when the initial orientation is completely unknown.

A Kalman/Particle Filter-Based Position and Orientation Estimation Method Using a Position Sensor/Inertial Measurement Unit Hybrid System

This work presents an efficient initial calibration and alignment algorithm for a 6-degrees of freedom inertial measurement unit (IMU) to be used in land vehicle applications. Error models for the gyros and accelerometers are presented with a study of their perturbation in trajectory prediction. A full inertial error model is also presented to determine the sensors needed for full observability of the different perturbation parameters. Finally, dead-reckoning experimental results are presented based on the initial alignment and calibration parameters obtained with the algorithms presented. The results show that the proposed algorithms provide accurate position and velocity information for an extended period of time using nonaided IMU. ©1999 John Wiley & Sons, Inc.

Initial calibration and alignment of low‐cost inertial navigation units for land vehicle applications

Extended Kalman filter synthesis for integrated global positioning/inertial navigation systems

A method for guiding a vehicle (30) to a target (28) includes furnishing a first vehicle (20) having a first global positioning system (GPS) receiver (24) fixed to receive global positioning signals from a selected constellation (46) of satellites in orbit above the earth and the second vehicle (30) having a second GPS receiver (32) fixed to receive global positioning signals from the same selected constellation (46) of GPS satellites. The first vehicle (20) locates the target (28) with an onboard sensor (26) and converts the location of the target (28) to the frame of reference of the selected constellation (46) of satellites of the GPS. The first vehicle (20) communicates this target position and the available set of GPS satellites to a navigation system of the second vehicle (30). The second vehicle (30) proceeds to the target location provided from the first vehicle (20) in the frame of reference of the GPS under control of its navigation system using the positioning signal derived from the second GPS receiver (32) fixed to receive positioning signals from the selected constellation (46) of satellites. In these operations, the second vehicle (30) remains within a sufficiently small operating distance of the position of the first vehicle (20) that variations in systematic bias errors between the first GPS receiver (24) and the second GPS receiver (32) are negligible.

Relative guidance using the global positioning system

This report describes the current state-of-the-art in Autonomous Land Vehicle (ALV) systems and technology. Five functional technology areas are identified and addressed. For each a brief, subjective, preface is first provided which envisions the necessary technology for the deployment of an operational ALV system. Subsequently, a detailed literature review is provided to support and elaborate these views. It is further established how these five technology areas fit together as a functioning whole. The essential conclusion of this report is that the necessary sensors, algorithms and methods to develop and demonstrate an operationally viable all-terrain ALV already exist and could be readily deployed. A second conclusion is that the successful development of an operational ALV system will rely on an effective approach to systems engineering. In particular, a precise description of mission requirements and a clear definition of component functionality is essential.

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A Critical Review of the State-of-the-Art in Autonomous Land Vehicle Systems and Technology

The Standoff Land Attack Missile (SLAM) is a worldwide, all-weather, precision-strike weapon system deployed from carrier-based aircraft. In the primary mode of operation, target location and other mission data are generated from intelligence sources available on the aircraft carrier and loaded into the missile prior to aircraft takeoff. After missile launch, the SLAM inertial navigation system (INS) guides the missile along the planned trajectory. Updating the missile INS from the Global Positioning System (GPS) during flight provides precise midcourse navigation and enhances target acquisition by accurate, on-target pointing of the SLAM Maverick seeker. The GPS/INS avionics and software integration used for SLAM are described in detail, along with some of the design tradeoffs that led to the approach. The avionics configuration integrates the Harpoon midcourse guidance unit, which includes a strapdown inertial sensor package and digital processor, with a Rockwell-Collins single-channel, sequential GPS receiver processor unit (RPU), a derivative of the GPS phase-III user equipment. In addition to the GPS receiver elements the RPU contains the navigation processor, which executes the SLAM navigation, Kalman filter algorithms, and other guidance algorithms including seeker pointing. Flight-test results of the SLAM GPS-aided INS are also included. >

G. Hyslop

Papers

GPS/INS integration on the Standoff Land Attack Missile (SLAM)