Geometric accuracy in airborne SAR images

Uncorrected across-track motions of a synthetic aperture radar (SAR) platform can cause both a severe loss of azimuthal positioning accuracy in, and defocusing of, the resultant SAR image. It is shown how the results of an autofocus procedure can be incorporated in the azimuth processing to produce a fully focused image that is geometrically accurate in azimuth. Range positioning accuracy is also discussed, leading to a comprehensive treatment of all aspects of geometric accuracy. The system considered is an X-band SAR     

Eigenstructure Assignment for Linear Systems

The use of feedback (full state, output, and constrained output) is considered as a means of shaping the transient response of linear time invariant systems. The underlying importance of the eigenstructure (eigenvalues/eigenvectors) is highlighted. Also, the important results and techniques are presented along with a brief literature review. An extensive flight control example is presented which should give direction to the application of eigenstructure assignment in diverse areas.     

A grid algorithm for autonomous star identification

An autonomous star identification algorithm is described that is simple and requires less computer resources than other such algorithms. In simulations using an 8/spl times/8 degree field of view (FOV), the algorithm identifies the correct section of sky on 99.7% of the sensor orientations where spatial accuracy of the imaged star is 1 pixel (56.25 arc seconds) in standard deviation and the apparent brightness deviates by 0.4 units stellar magnitude. This compares very favorably with other algorithms in the literature.     

Charge equalization for series-connected batteries

A novel nondissipative charge equalization circuit is proposed for charge equalization control of series-connected batteries. Each battery associates with a subcircuit, which is essentially a buck-boost converter acting as a current diverter to redistribute the excessive energy from more affluent batteries to the hungry ones. By dynamically redistributing the charging current, charge equalization can be achieved more quickly and efficiently. The applicability of this approach is confirmed by experiments.     

Evaluating the Detectability of Gaussian Stochastic Signals by Steepest Descent Integration

It is shown how to compute the detection probability of certain signals by numerical integration of the Laplace inversion integral involving the characteristic function or the moment-generating function of the detection statistic. The contour of integration is taken as the path of steepest descent of the integrand and is determined numerically as the integration proceeds. The method is applied to calculating the performance of the optimum detector of a Gaussian stochastic signal in white noise when the signals actually present have a different average s.n.r. from that assumed in the design. Results are presented for narrowband signals with Lorentz and rectangular spectral densities. The detectability of the former is shown to be more sensitive than that of the latter to the value of the design s.n.r. The relative disadvantage of the threshold detector, also assessed by this method, is smaller for signals with a rectangular than for those with a Lorentz spectral density.     

Sequential nonlinear tracking using UKF and raw range-rate measurements

The three-dimensional (3D) converted measurements filtering (CMF) with both converted position and raw range-rate measurement is proposed to solve the Doppler radar target tracking, where the error between radar-target range and range rate are correlated. Firstly, not using pseudomeasurement constructed by product of range and range rate to reduce the high nonlinearity, the raw range-rate measurements are utilized by unscented Kalman filter (UKF), where the converted errors of the position and the range rate are decorrelated, then linear part (position measurements) and nonlinear part (range-rate measurement) are sequentially processed by Kalman filter (KF) and UKF. Secondly, based on the assumption of small measurement error, the mean and covariance of converted measurement errors are derived by second-order Taylor series expansion. Finally, the influence of the correlated coefficient rho between the range and range rate, and the range-rate noise deviation sigma_r are taken into account and extreme values of rho and sigma_r are used in Monte Carlo simulations. The results show that the proposed method is, in a sense, effective and practical     

Implementing digital terrain data in knowledge-aided space-time adaptive processing

Many practical problems arise when implementing digital terrain data in airborne knowledge-aided (KA) space-time adaptive processing (STAP). This paper addresses these issues and presents solutions with numerical implementations. In particular, using digital land classification data and digital elevation data, techniques are developed for registering these data with radar return signals, correcting for Doppler and spatial misalignments, adjusting for antenna gain, characterizing clutter patches for secondary data selection, and ensuring independent secondary data samples. These techniques are applied to select secondary data for a single-bin post-Doppler STAP algorithm using multi-channel airborne radar measurement (MCARM) program data. Results with the KA approach are compared with those obtained using the standard sliding window method for choosing secondary data. These results illustrate the benefits of using terrain information, a priori data about the radar, and the importance of statistical independence when selecting secondary data for improving STAP performance     

The Coma of Comet 9P/Tempel 1

As comet 9P/Tempel 1 approaches the Sun in 2004–2005, a temporary atmosphere, or “coma,” will form, composed of molecules and dust expelled from the nucleus as its component icy volatiles sublimate. Driven mainly by water ice sublimation at surface temperatures T > 200 K, this coma is a gravitationally unbound atmosphere in free adiabatic expansion. Near the nucleus (≤ 10² km), it is in collisional equilibrium, at larger distances (≥10⁴ km) it is in free molecular flow. Ultimately the coma components are swept into the comet’s plasma and dust tails or simply dissipate into interplanetary space. Clues to the nature of the cometary nucleus are contained in the chemistry and physics of the coma, as well as with its variability with time, orbital position, and heliocentric distance. The DI instrument payload includes CCD cameras with broadband filters covering the optical spectrum, allowing for sensitive measurement of dust in the comet’s coma, and a number of narrowband filters for studying the spatial distribution of several gas species. DI also carries the first near-infrared spectrometer to a comet flyby since the VEGA mission to Halley in 1986. This spectrograph will allow detection of gas emission lines from the coma in unprecedented detail. Here we discuss the current state of understanding of the 9P/Tempel 1 coma, our expectations for the measurements DI will obtain, and the predicted hazards that the coma presents for the spacecraft. An erratum to this article is available at .     

Huygens' Surface Science Package

The design and performance of the Surface Science Package (SSP) on the Huygens probe are discussed. This instrument consists of nine separate sensors that are designed to measure a wide range of physical properties of Titan's lower atmosphere, surface, and sub-surface. By measuring a number of physical properties of the surface it is expected that the SSP will be able to constrain the inferred composition and structure of the moon's near-surface environment. Although the SSP is primarily designed to sense properties of the surface, some of its sensors will also make measurements of the atmosphere along the probe's entry path and will complement the data gathered by other experiments on the Huygens probe. This revised version was published online in August 2006 with corrections to the Cover Date.     

Hardware-Constrained Hybrid Coding of Video Imagery

The design, implementation, and performance of a video bandwidth compression system is described. In this system, compression is obtained by several methods including the use of DCT/DCPM hybrid coding, frame rate reduction, and resolution reduction. The overall compression ratio is up to 1000:1. The hardware-constrained design of the DCT and the DPCM is described and a new method is derived to solve the optimum integer bit-assignment problem associated with the block quantization process in the DPCM. Computer simulation results are presented which predict that the performance of the system using the derived optimal bit assignment method is superior to those obtained by other bit assignment methods. The real-time hybrid coding system design is optimized for a set of ?modified? average statistics to compress a wide variety of input video images. This approach eliminates the problem of nonzero dc mean value which could otherwise cause serious degradations in the system performance. The compression system is fully implemented and the quality of the reconstructed video as predicted by computer simulation has been demonstrated by the actual hardware performance. The PSNR of the reconstructed imagery is in excess of 36 dB at 2 bits per pixel.