Time domain maximum likelihood parameter estimation in LISA Pathfinder Data Analysis

Details Time domain maximum likelihood parameter estimation in LISA Pathfinder Data Analysis Time domain maximum likelihood parameter estimation in LISA Pathfinder Data Analysis

2011-08-03

arxiv.org/abs/1108.0862v1

Physics

Data Analysis, Statistics and Probability

16 pages (two columns), 15 figures, 5 tables, submitted to Phys. Rev. D

Scientific paper

LISA is the upcoming space-based Gravitational Wave telescope. LISA Pathfinder, to be launched in the coming years, will prove and verify the detection principle of the fundamental Doppler link of LISA on a flight hardware identical in design to that of LISA. LISA Pathfinder will collect a picture of all noise disturbances possibly affecting LISA, achieving the unprecedented pureness of geodesic motion necessary for the detection of gravitational waves. The first steps of both missions will crucially depend on a very precise calibration of the key system parameters. Moreover, robust parameters estimation is of fundamental importance in the correct assessment of the residual force noise, an essential part of the data processing for LISA. In this paper we present a maximum likelihood parameter estimation technique in time domain being devised for this calibration and show its proficiency on simulated data and validation through Monte Carlo realizations of independent noise runs. We discuss its robustness to non-standard scenarios possibly arising during the real-life mission, as well as its independence to the initial guess and non-gaussianities. Furthermore, we apply the same technique to data produced in mission-like fashion during operational exercises with a realistic simulator provided by ESA.

Affiliated with

Also associated with

No associations

Rating

Time domain maximum likelihood parameter estimation in LISA Pathfinder Data Analysis does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Time domain maximum likelihood parameter estimation in LISA Pathfinder Data Analysis, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Time domain maximum likelihood parameter estimation in LISA Pathfinder Data Analysis will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-664220