Design and implementation of near-field, wideband synthetic aperture beamformers

A coarray-based near-field, wideband synthetic aperture beamformer using stepped-frequency signal synthesis and post-data acquisition processing is presented. While coarray techniques offer significant reduction in the number of array elements for a given angular resolution, the hybrid subarray-stepped frequency realization of wideband systems simplifies implementations and offers flexibility in beamforming. Proof of concept is provided using real data collected in an anechoic chamber for several pulse shapes and array weightings.     

Robust adaptive beamforming for HF surface wave over-the-horizon radar

Adaptive beamforming is used to enhance the detection of target echoes received by high frequency (HF) surface wave (HFSW) over-the-horizon (OTH) radars in the presence of spatially structured interference. External interference from natural and man-made sources typically masks the entire range-Doppler search space and is characterized by a spatial covariance matrix that is time-varying or nonstationary over the coherent processing interval (CPI). Adaptive beamformers that update the spatial filtering weight vector within the CPI are likely to suppress such interference most effectively, but the intra-CPI antenna pattern fluctuations result in temporal decorrelation of the clutter which severely degrades subclutter visibility after Doppler processing. A robust adaptive beamformer that effectively suppresses spatially nonstationary interference without degrading subclutter visibility is proposed here. The proposed algorithm is computationally efficient and suitable for practical implementation. Its operational performance is evaluated using experimental data recorded by the Iluka HFSW OTH radar, located near Darwin in far north Australia.     

Exact multisensor dynamic bias estimation with local tracks

An exact solution is provided for the multiple sensor bias estimation problem based on local tracks. It is shown that the sensor bias estimates can be obtained dynamically using the outputs of the local (biased) state estimators. This is accomplished by manipulating the local state estimates such that they yield pseudomeasurements of the sensor biases with additive noises that are zero-mean, white, and with easily calculated covariances. These results allow evaluation of the Cramer-Rao lower bound (CRLB) on the covariance of the sensor bias estimates, i.e., a quantification of the available information about the sensor biases in any scenario. Monte Carlo simulations show that this method has significant improvement in performance with reduced rms errors of 70% compared with commonly used decoupled Kalman filter. Furthermore, the new method is shown to be statistically efficient, i.e., it meets the CRLB. The extension of the new technique for dynamically varying sensor biases is also presented.     

Performance evaluation for MAP state estimate fusion

This paper presents a quantitative performance evaluation method for the maximum a posteriori (MAP) state estimate fusion algorithm. Under ideal conditions where data association is assumed to be perfect, it has been shown that the MAP or best linear unbiased estimate (BLUE) fusion formula provides the best linear minimum mean squared estimate (LMMSE) given local estimates under the linear Gaussian assumption for a static system. However, for a dynamic system where fusion is recursively performed by the fusion center on local estimates generated from local measurements, it is not obvious how the MAP algorithm will perform. In the past, several performance evaluation methods have been proposed for various fusion algorithms, including simple convex combination, cross-covariance combination, information matrix, and MAP fusion. However, not much has been done to quantify the steady state behavior of these fusion methods for a dynamic system. The goal of this work is to present analytical fusion performance results for MAP state estimate fusion without extensive Monte Carlo simulations, using an approach developed for steady state performance evaluation for track fusion. Two different communication strategies are considered: fusion with and without feedback to the sensors. Analytic curves for the steady state performance of the fusion algorithm for various communication patterns are presented under different operating conditions.     

Robust model following control of parallel buck converters

A robust model-following (RMF) control technique for average current mode controlled (ACC) parallel buck dc-dc converters, RMFACC, is presented. RMFACC achieves that the loop gain of the voltage loop is little sensitive to the variation of power stage parameters: number of modules, input voltage, load, and component tolerances. The design of the voltage loop is 'decoupled' from the design of the disturbance rejection transfer functions in an important degree, so that the output impedance and audio susceptibility are greatly reduced without the need of high loop gain crossover frequencies. A comparative study between conventional ACC and RMFACC is shown.     

The Apollo SWC Experiment: Results,Conclusions, Consequences

Space Science Reviews - The Apollo Solar Wind Composition (SWC) experiment was designed to measure elemental and isotopic abundances of the light noble gases in the solar wind, and to investigate...     

Astrophysical implications of higher-dimensional gravity

We review the implications of modern higher-dimensional theories of gravity for astrophysics and cosmology. In particular, we discuss the latest developments of STM theory in connection with dark matter, particle dynamics and the cosmological constant, as well as related aspects of quantum theory. There are also more immediate tests of extra dimensions, notably involving perturbations of the cosmic 3K microwave background and the precession of a supercooled gyroscope in Earth orbit. We also outline some general features of embeddings, and include pictures of the big bang as viewed from a higher dimension.     

Toward Accurate On-Ground Attitude Determination for the Gaia Spacecraft

The work presented in this paper concerns the accurate On-Ground Attitude (OGA) reconstruction for the astrometry spacecraft Gaia in the presence of disturbance and of control torques acting on the spacecraft. The reconstruction of the expected environmental torques which influence the spacecraft dynamics will be also investigated. The telemetry data from the spacecraft will include the on-board real-time attitude, which is of order of several arcsec. This raw attitude is the starting point for the further attitude reconstruction. The OGA will use the inputs from the field coordinates of known stars (attitude stars) and also the field coordinate differences of objects on the Sky Mapper (SM) and Astrometric Field (AF) payload instruments to improve this raw attitude. The on-board attitude determination uses a Kalman Filter (KF) to minimize the attitude errors and produce a more accurate attitude estimation than the pure star tracker measurement. Therefore the first approach for the OGA will be an adapted version of KF. Furthermore, we will design a batch least squares algorithm to investigate how to obtain a more accurate OGA estimation. Finally, a comparison between these different attitude determination techniques in terms of accuracy, robustness, speed and memory required will be evaluated in order to choose the best attitude algorithm for the OGA. The expected resulting accuracy for the OGA determination will be on the order of milli-arcsec.     

The Lunar Reconnaissance Orbiter Miniature Radio Frequency (Mini-RF) Technology Demonstration

The Miniature Radio Frequency (Mini-RF) system is manifested on the Lunar Reconnaissance Orbiter (LRO) as a technology demonstration and an extended mission science instrument. Mini-RF represents a significant step forward in spaceborne RF technology and architecture. It combines synthetic aperture radar (SAR) at two wavelengths (S-band and X-band) and two resolutions (150 m and 30 m) with interferometric and communications functionality in one lightweight (16 kg) package. Previous radar observations (Earth-based, and one bistatic data set from Clementine) of the permanently shadowed regions of the lunar poles seem to indicate areas of high circular polarization ratio (CPR) consistent with volume scattering from volatile deposits (e.g. water ice) buried at shallow (0.1–1 m) depth, but only at unfavorable viewing geometries, and with inconclusive results. The LRO Mini-RF utilizes new wideband hybrid polarization architecture to measure the Stokes parameters of the reflected signal. These data will help to differentiate “true” volumetric ice reflections from “false” returns due to angular surface regolith. Additional lunar science investigations (e.g. pyroclastic deposit characterization) will also be attempted during the LRO extended mission. LRO’s lunar operations will be contemporaneous with India’s Chandrayaan-1, which carries the Forerunner Mini-SAR (S-band wavelength and 150-m resolution), and bistatic radar (S-Band) measurements may be possible. On orbit calibration, procedures for LRO Mini-RF have been validated using Chandrayaan 1 and ground-based facilities (Arecibo and Greenbank Radio Observatories).     

Characteristics of Icy Surfaces

The surfaces of the Solar System’s icy satellites show an extraordinary variety of morphological features, which bear witness to exchange processes between the surface and subsurface. In this paper we review the characteristics of surface features on the moons of Jupiter, Saturn, Uranus and Neptune. Using data from spacecraft missions, we discuss the detailed morphology, size, and topography of cryovolcanic, tectonic, aeolian, fluvial, and impact features of both large moons and smaller satellites.