Obstacle Tracking Results: Cartesian vs. Spherical Particle Filter
نویسندگان
چکیده
This paper focuses on test results from an Airborne Obstacle Tracking system for Unmanned Aerial System (UAS) See and Avoid applications that is based on Particle Filtering algorithm. It performs data fusion of airborne forward looking radar and electro-optical camera by exploiting data gathered during a Sense and Avoid flight experiment at Italian Aerospace Research Centre (CIRA). The developed model resulted adequate for tracking aircraft trajectories, thus overcoming the non-gaussian and nonlinear form of the most widely adopted target dynamics models.
منابع مشابه
A New Modified Particle Filter With Application in Target Tracking
The particle filter (PF) is a novel technique that has sufficiently good estimation results for the nonlinear/non-Gaussian systems. However, PF is inconsistent that caused mainly by loss of particle diversity in resampling step and unknown a priori knowledge of the noise statistics. This paper introduces a new modified particle filter called adaptive unscented particle filter (AUPF) to overcome th...
متن کاملA Tracking Filter in Spherical Coordinates Enhanced by De-noising of Converted Doppler Measurements
Tracking problem in spherical coordinates with range rate (Doppler) measurements, which would have errors correlated to the range measurement errors, is investigated in this paper. The converted Doppler measurements, constructed by the product of the Doppler measurements and range measurements, are used to replace the original Doppler measurements. A de-noising method based on an unbiased Kalma...
متن کاملAn Efficient Target Tracking Algorithm Based on Particle Filter and Genetic Algorithm
In this paper, we propose an efficient hybrid Particle Filter (PF) algorithm for video tracking by employing a genetic algorithm to solve the sample impoverishment problem. In the presented method, the object to be tracked is selected by a rectangular window inside which a few numbers of particles are scattered. The particles’ weights are calculated based on the similarity between feature vecto...
متن کاملBest Linear Unbiased Filtering for Target Tracking with Spherical Measurements
In tracking applications, target dynamics is usually modeled in the Cartesian coordinates, while target measurements are directly available in the original sensor coordinates. Measurement-conversion is widely used such that the Kalman filter can be applied in the Cartesian coordinates. A number of improved measurement-conversion techniques have been proposed recently. However, they have fundame...
متن کاملStereo-Based Tracking-by-Multiple Hypotheses Framework for Multiple Vehicle Detection and Tracking
In this paper, we present a tracking‐by‐multiple hypotheses framework to detect and track multiple vehicles accurately and precisely. The tracking‐by‐ multiple hypotheses framework consists of obstacle detection, vehicle recognition, visual tracking, global position tracking, data association and particle filtering. The multiple hypotheses are from obstacle detect...
متن کامل