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This paper investigates on the development and implementation of a high integrity navigation system based on the combined use of the Global Positioning System (GPS) and an inertial measurement unit (IMU) for land vehicle applications. The complementary properties of the GPS and the INS have motivated several works dealing with their fusion by using a Kalman Filter. The conventional kalman filter has...
A decentralized estimation architecture for determining an object's absolute position from relative position measurements, commonly called geolocation, is developed in this paper. Relative measurements are obtained from a two unmanned aerial vehicle (UAV) team with electronic support measure (ESM) sensors on board. One team combines their time of arrival (TOA) measurements forming one time difference...
In this paper the Kalman filter equations are re- derived for systems with mobile sensors. The motion of the sensor impacts the measurement noise statistical properties through the measurement covariance matrix and, consequently, the estimation error covariance matrix. Moreover, since the sensors are mobile, their motion has an associated control cost. Minimizing the control effort expended during...
This paper addresses the problem of resource allocation in formations of mobile robots localizing as a group. Each robot receives measurements from various sensors that provide relative (robot-to-robot) and absolute positioning information. Constraints on the sensors' bandwidth, as well as communication and processing requirements, limit the number of measurements that are available or can be processed...
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