An Unmanned Aircraft System (UAS) collision avoidance algorithm for the Sense and Avoid (SAA) problem is proposed. The avoidance path is modeled using a physical analogy of a chain placed in a force field. This approach has the advantage that it continuously searches the space for a proper evasive maneuver to avoid an impending collision with detected intruding aircraft while observing the standard flight rules followed by manned aircraft. The algorithm also accounts for the uncertainties associated with the intruder aircraft's state estimates computed by the detection algorithm. To examine the proposed avoidance algorithm we combined the electro-optical (EO) based Monocular Maneuverless PAssive Ranging System (M2PARS) technology developed by UtopiaCompression Corporation (UC) for detecting imminent collisions using passive imaging sensors and simulated the integrated model to predesigned encounter geometry scenarios in the Matlab/Simulink environment.
As autonomous navigation becomes considerable and important because of the increased demand to their usage and benefits, therefore reliability and integrity issues become definite, specially when being implemented with commercially low-cost sensors. The objective of this thesis is to both develop and implement in real-time an INS/GPS integrated navigation system using the loosely-coupled linear Kalman filter. The importance of the implemented algorithms are to function appropriately and accurately using low cost inertial sensors where the rapid drift in sensors output requires a reliance on external and available aiding source as Global Positioning System (GPS).This thesis describes the theoretical development and practical implementation in real-time of strapdown inertial navigation system (INS) using commercial of the shelf low cost inertial measurement unit (IMU) aided with the Global Positioning System (GPS). When describing the IMU as a "low cost", this term means that this unit is built using standard low grade accelerometers and gyros which cannot conduct self-alignment. Therefore the thesis provides a desirable calibration procedure where the requirements of a precisely controlled orientation of the IMU can be relaxed. To do so, the thesis describes in detail the design, construction, error modelling analysis and calibration approach of six-degree of freedom (6DOF) IMU. On the other hand, calibration of (IMU) unit is one of the most challenging issues in navigation field as it requires high accuracy measurements in order to maintain acceptable readings from sensors, and normally the cost of calibration platform often exceeds the cost of developing and constructing a MEMS sensor based IMU.This thesis mainly discusses the development of inertial mechanization equations and algorithms that provides position, velocity and attitude of the host platform. Then, the data provided by inertial navigation mechanization is fused with GPS measurements using loosely-coupled linear. The accuracy of the estimation when utilizing a low-cost inertial navigation system (INS) is limited by the accuracy of the used sensors and the mathematical modelling of INS and the aiding sensors errors, however iii when fusing the INS data with GPS data, the errors can be bounded and the accuracy will increase. This thesis provides, both in practical and theoretical terms, the fusion processes adopted and real time implementation required for a high integrity aided inertial navigation system using state-of-art technology microcontroller MPC555 as the navigation computer. The theoretical work is verified by set of real-time experiments using our developed INS/GPS equipment -The developed IMU, standard GPS and MPC555-, the results have been compared with a top-notch INS/GPS Navigation device. The experimental results using our designed INS/GPS has shown that position and velocity accuracy can be archived using algorithms presented in this thesis work.iv
As autonomous navigation becomes considerable and important because of the increased demand to their usage and benefits, therefore reliability and integrity issues become definite, specially when being implemented with commercially low-cost sensors. The objective of this thesis is to both develop and implement in real-time an INS/GPS integrated navigation system using the loosely-coupled linear Kalman filter. The importance of the implemented algorithms are to function appropriately and accurately using low cost inertial sensors where the rapid drift in sensors output requires a reliance on external and available aiding source as Global Positioning System (GPS).This thesis describes the theoretical development and practical implementation in real-time of strapdown inertial navigation system (INS) using commercial of the shelf low cost inertial measurement unit (IMU) aided with the Global Positioning System (GPS). When describing the IMU as a "low cost", this term means that this unit is built using standard low grade accelerometers and gyros which cannot conduct self-alignment. Therefore the thesis provides a desirable calibration procedure where the requirements of a precisely controlled orientation of the IMU can be relaxed. To do so, the thesis describes in detail the design, construction, error modelling analysis and calibration approach of six-degree of freedom (6DOF) IMU. On the other hand, calibration of (IMU) unit is one of the most challenging issues in navigation field as it requires high accuracy measurements in order to maintain acceptable readings from sensors, and normally the cost of calibration platform often exceeds the cost of developing and constructing a MEMS sensor based IMU.This thesis mainly discusses the development of inertial mechanization equations and algorithms that provides position, velocity and attitude of the host platform. Then, the data provided by inertial navigation mechanization is fused with GPS measurements using loosely-coupled linear. The accuracy of the estimation when utilizing a low-cost inertial navigation system (INS) is limited by the accuracy of the used sensors and the mathematical modelling of INS and the aiding sensors errors, however iii when fusing the INS data with GPS data, the errors can be bounded and the accuracy will increase. This thesis provides, both in practical and theoretical terms, the fusion processes adopted and real time implementation required for a high integrity aided inertial navigation system using state-of-art technology microcontroller MPC555 as the navigation computer. The theoretical work is verified by set of real-time experiments using our developed INS/GPS equipment -The developed IMU, standard GPS and MPC555-, the results have been compared with a top-notch INS/GPS Navigation device. The experimental results using our designed INS/GPS has shown that position and velocity accuracy can be archived using algorithms presented in this thesis work.iv
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