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A parametric estimation algorithm for a single-axis gradiometer is described. The most influential parameters are isolated and estimated; their bias and variance are discussed. Even though the system is closed-loop controlled, only plant parameters are estimated using an open-loop identification equation, which simplifies the identification procedure. The estimates are obtained using the method of instrumental variables (IV). The advantage of this method is that it remains bias-free even when the system states are correlated with the measurement noise. The problem is described in a one-dimensional frame, but it can be extended to the multivariate case if necessary. The estimated parameters are then used to reconstitute the closed-loop transfer function, which allows the input disturbance that caused the observed signal to be deduced. The estimation algorithm is applied to the laser interferometer space antenna (LISA) technology package, which is the scientific payload of the LISA Pathfinder spacecraft (SC), an ESA/NASA technology demonstrator to be launched in 2014. The analysis is operated on a simulated dataset produced with the mission end-to-end simulator (E2E) as well as with a simple linear simulator. The on-board software and hardware constraints are taken into account since they are important performance drivers. The results are detailed along with the experiment model. [ABSTRACT FROM PUBLISHER]

The LISA Pathfinder Drift Mode is an experimental mode proposed for the LISA Pathfinder drag free space mission. The Drift Mode’s specificity is to switch off a possibly noisy actuator periodically in order to minimize the actuation noise. The experiment delivers a measurement that includes data segments virtually free of any actuation force noise. The corresponding acceleration data is then used to estimate the experiment disturbance spectrum, using a calibrating and gap-filling algorithm. This article focuses on two points to demonstrate the feasibility and interest of such an experiment: a first part is dedicated to experiment control and dynamics, whereas the second part explains how to solve the challenging problem posed by the data analysis. [ABSTRACT FROM AUTHOR]

The drag-free experiment on-board LISA Pathfinder, the LISA Technology Package (LTP), has for its main science mission the proof of a low disturbance noise level. It is measured differentially between two test-masses whose relative motion is perturbed by their respective capacitive actuator noise. In order to suppress this noise source the drift mode actuation scheme uses very short impulses to produce kicks. This way the test-masses motion between two kicks is a free parabolic flight and can be used for a spectral estimation of the remaining noise sources, allowing us to distinguish between external noise sources and actuation noise. This mode will be helpful in the case of a high actuation noise or to investigate some unexpected external noise source, but the foremost reason being that this experiment is closer to the ultimate LISA experiment in terms of actuation noise. It must be implemented on-board taking into account the constraints of a space-borne experiment in terms of robustness, usability and existing software and hardware architecture. [ABSTRACT FROM AUTHOR]

The data analysis of the LISA Technology Package (LTP) will comprise a series of discrete experiments, each focusing on a particular noise measurement or characterization of the instrument in various operating modes. Each of these experiments must be analysed and planned in advance of the mission because the results of a given experiment will have an impact on those that follow. As such, a series of mock data challenges (MDCs) will be developed and carried out with the aim of preparing the analysis tools and optimizing the various planned analyses. The first of these MDCs (MDC1) is a simplified treatment of the dynamics along the axis joining the two test masses onboard LISA Pathfinder. The validation of the dynamical model by predicting the spectra of the interferometer output data is shown, a prediction for the data analysis is calculated and, finally, several simulated interferometer data sets are analysed and calibrated to equivalent out-of-loop test mass acceleration. [ABSTRACT FROM AUTHOR]