Synthetic-aperture radar processing using fast factorized back-projection

Exact synthetic aperture radar (SAR) inversion for a linear aperture may be obtained using fast transform techniques. Alternatively, back-projection integration in time domain can also be used. This technique has the benefit of handling a general aperture geometry. In the past, however, back-projection has seldom been used due to heavy computational burden. We show that the back-projection integral can be recursively partitioned and an effective algorithm constructed based on aperture factorization. By representing images in local polar coordinates it is shown that the number of operations is drastically reduced and can be made to approach that of fast transform algorithms. The algorithm is applied to data from the airborne ultra-wideband CARABAS SAR and shown to give a reduction in processing time of two to three orders of magnitude.     

Almost instant time inference for hybrid partially dynamic Bayesian networks

A Bayesian network (BN) is a compact representation for probabilistic models and inference. They have been used successfully for many military and civilian applications. It is well known that, in general, the inference algorithms to compute the exact a posterior probability of a target node given observed evidence are either computationally infeasible for dense networks or impossible for general hybrid networks. In those cases, one either computes the approximate results using stochastic simulation methods or approximates the model using discretization or a Gaussian mixture model before applying an exact inference algorithm. This paper combines the concept of simulation and model approximation to propose an efficient algorithm for those cases. The main contribution here is a unified treatment of arbitrary (nonlinear non-Gaussian) hybrid (discrete and continuous) BN inference having both computation and accuracy scalability. The key idea is to precompile the high-dimensional hybrid distribution using a hypercube representation and apply it for both static and dynamic BN inference. Since the inference process essentially becomes a combination of table look-up and some simple operations, the method is shown to be extremely efficient. It can also he scaled to achieve any desirable accuracy given sufficient preprocessing time and memory for the cases where exact inference is not possible     

Recent Breakthroughs in RF Photonics for Radar Systems

Radar systems require transmission of very high purity signals. Photonics is now mature enough to achieve analog transmission with very low noise, strong immunity, and wide-bandwidth even in harsh environments. We present our recent developments of optimized optical links dedicated to radar and multifunction systems     

Subspace array processing for the suppression of FM jamming in GPS receivers

The mitigation of FM interference in GPS receivers is considered. In difference to commonly assumed wideband and narrowband interferers, the FM interferers are wideband, but instantaneously narrowband, and as such, have clear time-frequency (TF) signatures that are distinct from the GPS coarse acquisition (C/A) spread spectrum code. In the proposed technique, the estimate of the FM interference instantaneous frequency (IF) and the interference spatial signature are used to construct the spatiotemporal interference subspace. The IF estimates can be provided using existing effective linear or bilinear TF methods. The undesired signal arrival is suppressed by projecting the input data on the interference orthogonal subspace. With a multisensor receiver, the distinctions in both the spatial and TF signatures of signal arrivals allow effective interference suppressions. The deterministic nature of the signal model is considered and the known underlying structure of the GPS C/A code is utilized. We derive the receiver signal-to-interference-plus-noise ratio (SINR) under exact and perturbed IF values. The effect of IF estimation errors on both pseudorange measurements and navigation data recovery is analyzed. Simulation results comparing the receiver performances under IF errors in single and multiantenna GPS receivers are provided.     

HMS SCOTT ring laser gyro navigator integration

HMS SCOTT is a United Kingdom ocean survey vessel that hosts a state-of-the-art deep ocean mapping system which was designed, developed, and is currently maintained and periodically updated by the Space and Naval Warfare Systems Center, San Diego, (SSC San Diego). A recent update of this system consisted of the replacement of an obsolete and very costly to maintain inertial navigation system. Another reason for updating the ship's inertial system was to provide higher accuracy attitude data, than was previously available with the old inertial system, to the high resolution multi-beam sonar system in order to produce improved bathymetric charts. After conducting a market survey of suitable inertial navigator systems, the Kearfott SEANAV ring laser gyro navigator (RLGN) system, using a monolithic T-24 gyro, was selected to replace the old inertial system. The selection of the SEANAV RLGN was based on its relatively low cost, high reliability, and, particularly, the roll and pitch data accuracies of typically less than 1-arc-minute. This attitude data accuracy was key to enable a significant improvement in the bathymetry data accuracy. Two SEANAV systems were integrated with GPS receivers, a system master time code generator, and electro magnetic (EM) log and Doppler sonar speed sensors to provide the navigation portion of the mapping data. Operational testing of this updated system aboard HMS SCOTT, in November, 2003, showed a marked improvement in the quality of the map product due, in part, to the improved attitude data provided by the SEANAV RLGN system.     

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.     

Reduced-order multiple model adaptive controller for flexiblespacestructure

The robustness of a moving-bank multiple model adaptive estimator/controller to order reduction in the controller design model is examined. It is shown that the adaptive mechanism and bank-moving logic are not confounded by the effects of unmodeled higher order modes of a large flexible spacestructure. Control characteristics are achieved that are essentially equivalent to those of an artificially informed benchmark controller     

Carbon dioxide and oxygen budgets of a plant cultural system in a CELSS--a case of cultivation of lettuce and turnips.

In order to collect basic data about CO2 and O2 budgets of a plant cultural system in a CELSS, the variation of the CO2 absorption rates of lettuce and turnips were observed during the growing period, under different conditions. The O2 release rates were deduced from the CO2 absorption rates multiplied by 32/44. As a result, when the light intensity, the photoperiod and the atmospheric CO2 concentration increased, the rates also increased. The effects on the turnips were more significant than those on the lettuce. Turnips at 310 micromoles/m2/s of PPFD, 24 hours of photoperiod and 1100 ppm of CO2 concentration grew most actively in the present experimental conditions. One turnip absorbed 32.3 g CO2 and released 23.5 g O2 for 6 days between 24 days and 30 days after sowing.     

First estimations of the aerosol optical thickness using Langley Method at Southern Brazil (29.4°S, 53.8°W)

The first estimations of the aerosol optical thickness (AOT) using Langley Method at Southern Space Observatory (SSO) at Southern Brazil (29.4°S, 53.8°W) are presented. In addition to ozone and sulphur dioxide columns, AOT can be obtained using Brewer Spectrophotometer at specific wavelengths: 306.3, 310.1, 313.5, 316.8 and 320.1 nm. The AOT was obtained for the period from November/2002 to May/2003. Very low AOT averages were obtained, whose values were about 0.21 ± 0.03 at 306.3 nm, 0.21 ± 0.02 at 310.1 nm, 0.19 ± 0.02 at 313.5 nm, 0.20 ± 0.02 at 316.8 nm and 0.20 ± 0.02 at 320.0 nm for all period analysed. Different behaviour of AOT were obtained at two daily specific periods of aerosol accumulation, one in the afternoons from November/2002 to February/2003, caused mainly by a mild biomass burning season’s in the region and other in the mornings from March to May/2003, due the high relative humidity presented in the region studied.