The Radarsat Antarctic Mapping Mission

The Radarsat Earth-observation satellite was launched on November 4, 1995 aboard a Delta 2 rocket. Equipped with a sophisticated synthetic aperture radar (SAR), Radarsat can produce images of extraordinary clarity even through clouds, smog, haze, smoke, and darkness. The SAR has a variety of operating modes. It can be adjusted to produce swathes between 35 and 500 km in width, with ground resolutions from 100 m to as low as eight. In addition, the beam can be steered at angles up to 49° from the satellite's nadir vector, giving it the unique ability to image areas it is not directly overflying. In exchange for the launch, CSA agreed to provide NASA with access to the SAR data, and to execute a 180° yaw-around of Radarsat twice during its lifetime to map the Antarctic continent. Preliminary results from the first of these Antarctic Mapping Missions, dubbed AMM-1, are presented     

Advanced materials for next generation NiMH portable, HEV and EVbatteries

While Ovonic NiMH batteries are already in high volume commercial production for portable applications, advances in materials technology have enabled performance improvements in specific energy (100 Wh/kg), specific power (600-1000 W/kg), high temperature operation, charge retention, and voltage stability. Concurrent with technology advances, Ovonic NiMH batteries have established performance and commercial milestones in electric vehicles, hybrid electric vehicles, as well as scooter, motorcycle and bicycle applications. As important as these advances, significant manufacturing cost reductions have also occurred which allow continued growth of NiMH technology. In this paper, advances in performance, applications and cost reduction are discussed with particular emphasis on the improved proprietary metal hydride and nickel hydroxide materials that make such advances possible     

Sensor alignment with Earth-centered Earth-fixed (ECEF) coordinatesystem

In this work, we formulate the multiple sensor alignment problem in an Earth-centered Earth-fixed (ECEF) coordinate system. The alignment algorithm maps the sensor measurements to the ECEF coordinates using a geodetic transformation, and attributes the discrepancies in the Earth-referenced system reported by each sensor to the sensor biases. Sensor biases are then estimated using the least squares (LS) technique. Simulated and real-life radar data are used to evaluate the performance of the proposed algorithm. Comparisons are made to those algorithms based on the standard stereographic projection     

Structures for radar detection in compound Gaussian clutter

The problem of coherent radar target detection in a background of non-Gaussian clutter modeled by a compound Gaussian distribution is studied here. We show how the likelihood ratio may be recast into an estimator-correlator form that shows that an essential feature of the optimal detector is to compute an optimum estimate of the reciprocal of the unknown random local power level. We then proceed to show that the optimal detector may be recast into yet another form, namely a matched filter compared with a data-dependent threshold. With these reformulations of the optimal detector, the problem of obtaining suboptimal detectors may be systematically studied by either approximating the likelihood ratio directly, utilizing a suboptimal estimate in the estimator-correlator structure or utilizing a suboptimal function to model the data-dependent threshold in the matched filter interpretation. Each of these approaches is studied to obtain suboptimal detectors. The results indicate that for processing small numbers of pulses, a suboptimal detector that utilizes information about the nature of the non-Gaussian clutter can be implemented to obtain quasi-optimal performance. As the number of pulses to be processed increases, a suboptimal detector that does not require information about the specific nature of the non-Gaussian clutter may be implemented to obtain quasi-optimal performance     

An interior point linear programming approach to two-scan dataassociation

We present an efficient two-scan data association method (TSDA) based on an interior point linear programming (LP) approach. In this approach, the TSDA problem is first formulated as a 3-dimensional assignment problem, and then relaxed to a linear program; the latter is subsequently solved by the highly efficient homogeneous, self-dual interior point LP algorithm. When the LP algorithm generates a fractional optimal solution, we use a technique similar to the joint probabilistic data association method (JPDA) to compute a weighted average of the resulting fractional assignments, and use it to update the states of the existing tracks generated by Kalman filters. Unlike the traditional single scan JPDA method, our TSDA method provides an explicit mechanism for track initiation. Extensive computer simulations have demonstrated that the new TSDA method is not only far more efficient in terms of low computational complexity, but also considerably more accurate than the existing single-scan JPDA method     

Estimating matched filter amplitude probability functions byfailure rate analysis

Performance analysis of echolocation systems requires knowledge of the probability density function (pdf) or cumulative distribution function (cdf) of a matched filter output. A method is presented to estimate these and other probability functions from data by estimating the failure rate function, a function employed in reliability theory. The method can also be used to derive approximations to closed-form probability functions. The method is demonstrated using experimental sonar and radar clutter data and a closed-form radar clutter model     

Analysis and results of the 1995 Yuma ground penetration SARmeasurements

In July and October 1995, a large-scale airborne SAR experiment was conducted in the Yuma Proving Ground, Yuma, Arizona, to investigate ground penetration radar phenomenology and buried target detection. This paper describes the Yuma experiment and measurement results for many tactical, utility, and environmental targets deployed in the test     

Analysis of an adaptive CFAR detector in non-Gaussian interference

Coherent signal detection in non-Gaussian interference is presently of interest in adaptive array applications. Conventional array detection algorithms inherently model the interference with a multivariate Gaussian random vector. However, non-Gaussian interference models are also under investigation for applications where the Gaussian assumption may not be appropriate. We analyze the performance of an adaptive array receiver for signal detection in interference modeled with a non-Gaussian distribution referred to as a spherically invariant random vector (SIRV). We first motivate this interference model with results from radar clutter measurements collected in the Mountain Top Program. Then we develop analytical expressions for the probability of false alarm and the probability of detection for the adaptive array receiver. Our analysis shows that the receiver has constant false alarm rate (CFAR) performance with respect to all the interference parameters. Some illustrative examples are included that compare the detection performance of this CFAR receiver with a receiver that has prior knowledge of the interference parameters     

Highly accurate, noncoherent technique for spacecraft Dopplertracking

A two-way, noncoherent spacecraft navigation technique has been developed to provide velocity accuracy comparable to that available from a deep space coherent transponder (0.1 mm/s). The technique is compatible with the normal tracking procedures of the Deep Space Network (DSN) ground stations and does not require the use of a highly stable oscillator on-board the spacecraft. The measurement technique, potential error sources, and test results obtained with prototype hardware are described