Space base laser torque applied on LEO satellites of various geometries at satellite’s closest approach

Khalifa, N. S.

doi:10.1016/j.nrjag.2013.12.004

Cited by 2 publications

(1 citation statement)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The targets information such as its relative range, azimuth and elevation, as well as its velocity is the primary sensor data necessary for tracking. Based on the type of scenario different tracking methodologies can be employed with different sensor technologies (Rodríguez-Canosa et al, 2014;Khalifa, 2013;Landsat 8, 2013). For instance, network centric warfare is one of the key components of Department of Defence for the US forces to enhance the situational awareness in the battle space (Friedman, 2009).…”

Section: Introductionmentioning

confidence: 99%

State Estimation based Target Tracking and Applications of Multi Sensor Data Fusion

Kondru

Celenk

Shen

2019

IJFSE

View full text Add to dashboard Cite

Detection, discrimination and tracking of a target under a given dynamic environment is one of the main challenges of an integrated sensory system. A combination of two or more sensors will always provide a better position estimate rather than a single sensor. The advantages of multi-sensor data fusion over a conventional single sensor tracking are presented in this paper. Using state estimators from simple linear rustic filters to a complex nonlinear filter, the tracking of target performing three different motions with sensor noises are presented in this paper. RADAR and the infrared search and track (IRST) are the two sensors considered based on which a complete mathematical modelling and simulation of the sensor measurements and tracking methodologies are utilised. The extension of the paper also presents the image fusion techniques using a widely known technique known as principle component analysis method. The RMS errors in position as well as image error measurements are performed that shows the superiority of the multi sensor data fusion process.

show abstract

Section: Introductionmentioning

confidence: 99%