This paper presents an algorithm for the classification of targets based on the fusion of the class information provided by different imaging sensors. The outputs of the different sensors are combined to obtain an accurate estimate of the target class. The performance of each imaging sensor is modelled by means of its confusion matrix (CM), whose elements are the conditional error probabilities in the classification and the conditional correct classification probabilities. These probabilities are used by each sensor to make a decision on the target class. Then, a final decision on the class is made using a suitable fusion rule in order to combine the local decisions provided by the sensors. The overall performance of the classification process is evaluated by means of the “fused” confusion matrix, i.e. the CM pertinent to the final decision on the target class. Two fusion rules are considered: a majority voting (MV) rule and a maximum likelihood (ML) rule. A case study is then presented, where the developed algorithm is applied to three imaging sensors located on a generic air platform: a video camera, an infrared camera (IR), and a spotlight Synthetic Aperture Radar (SAR).

S. Giompapa

A. Farina

F. Gini

A. Graziano

R. Croci

R. Di Stefano

Naval Target Classification by Fusion of Multiple Imaging Sensors Based on the Confusion Matrix

Traditionally the 
                  relative positioning and attitude determination 
                  problem are treated as independent. In this 
                  contribution we will investigate the 
                  possibilities of using multiantenna (i.e., triple and 
                  quadruple) data, not only for attitude 
                  determination but also for relative 
                  positioning. The methods developed are rigorous 
                  and have the additional advantage that they 
                  improve ambiguity resolution on the 
                  unconstrained baseline(s) and the overall 
                  success rate of ambiguity resolution between a 
                  number of antennas.

Peter J. Buist

Peter J. G. Teunissen

Gabriele Giorgi

Sandra Verhagen

Multiplatform Instantaneous GNSS Ambiguity Resolution for Triple- and Quadruple-Antenna Configurations with Constraints

A real-time algorithm to detect, determine, and validate the cycle-slips for triple-frequency GPS is proposed. The cycle-slip detection is implemented by simultaneously applying two geometry-free phase combinations in order to detect more insensitive cycle-slips, and it is applicable for high data rate applications. The cycle-slip determination adaptively uses the predicted phase data and the code data. LAMBDA technique is applied to search for the cycle-slip candidates. The cycle-slip validation provides strict test criteria to identify the cycle-slip candidates under low phase noise. The reliability of the proposed algorithms is tested in different simulated scenarios.

Zhen Dai

Stefan Knedlik

Otmar Loffeld

Instantaneous Triple-Frequency GPS Cycle-Slip Detection and Repair

Global position system (GPS) is being widely used in land vehicles to provide positioning information. However, in urban canyons, rural tree canopies, and tunnels, the GPS satellite signal is usually blocked and there is an interruption in the positioning information. To obtain positioning solution during GPS outages, GPS can be augmented with an inertial navigation system (INS). However, the utilization of full inertial measurement unit (IMU) in land vehicles could be quite expensive despite the use of the microelectromechanical system (MEMS)-based sensors. Contemporary research is focused on reducing the number of inertial sensors inside an IMU. This paper explores a multisensor system (MSS) involving single-axis gyroscope and an odometer to provide full 2D positioning solution in denied GPS environments. Furthermore, a Kalman filter (KF) model is utilized to predict and compensate the position errors of the proposed MSS. The performance of the proposed method is examined by conducting several road tests trajectories using both MEMS and tactical grade inertial sensors. It was found that by using proposed MSS algorithm, the positional inaccuracies caused by GPS signal blockages are adequately compensated and resulting positional information can be used to steer the land vehicles during GPS outages with relatively small position errors.

Umar Iqbal

Tashfeen B. Karamat

Aime F. Okou

Aboelmagd Noureldin

Experimental Results on an Integrated GPS and Multisensor System for Land Vehicle Positioning

This paper presents an evaluation of several GNSS multicarrier ambiguity (MCAR) resolution techniques for the purpose of attitude determination of low earth orbiting satellites (LEOs). It is based on the outcomes of the study performed by the University of Calgary and financed by the European 6th Framework Programme for Research and Development as part of the research project PROGENY. The existing MCAR literature is reviewed and eight possible variations of the general MCAR processing scheme are identified based on two possible options for the mathematical model of the float solution, two options for the estimation technique used for the float solution, and finally two possible options for the ambiguity resolution process. The two most promising methods, geometry-based filtered cascading and geometry-based filtered LAMBDA, are analysed in detail for two simulated users modelled after polar orbiting LEOs through an extensive covariance simulation. Both the proposed Galileo constellation and Galileo used in conjunction with the GPS constellation are tested and results are presented in terms of probabilities of correct ambiguity resolution and float and fixed solution baseline accuracies. The LAMBDA algorithm is shown to outperform the cascading method, particularly in the single-frequency dual-GNSS system case. Secondly, more frequencies and multiple GNSS always offer improvement, but the single-frequency dual-system case is found to have similar performance to the dual-frequency single-system case.

Kyle O'Keefe

Mark Petovello

Wei Cao

G&#xe9;rard Lachapelle

Eric Guyader

Comparing Multicarrier Ambiguity Resolution Methods for Geometry-Based GPS and Galileo Relative Positioning and Their Application to Low Earth Orbiting Satellite Attitude Determination

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International Journal of Navigation and Observation - Table of contents 2009

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