Multipath interferometry technique for airborne array calibration

A new technique is developed to compensate multiple-wavelength distortion in airborne antenna arrays. This approach exploits the phase information in microwave reflections from arbitrary terrain. To handle reflections incident over a broad angle, a range-Doppler preprocessor is used in each element channel to resolve wavefronts incident simultaneously from different directions. The phase information for each direction of arrival is compared between elements and processed by optimal estimators to determine the phase corrections needed to compensate the distortion. To develop the estimators, a statistical model of the complex baseband terrain reflections is developed. This is in turn used to generate conditional probability densities involving the range Doppler observations and the parameters to be estimated. These densities are subsequently used to develop minimum variance and maximum likelihood estimators. The new estimators use additional information that has not been exploited by previous techniques and therefore provide enhanced performance     

Localization performance of arrays subject to phase errors

The passive localisation of radiating sources using an array subject to random perturbations in sensor phases is presented. All source signals as well as additive noises observed at the sensors are assumed to be independent identically distributed zero-mean Gaussian random processes. Cramer-Rao bounds are derived for source bearings and ranges for the phase errors at each sensor. It is shown that accurate phase calibration can be achieved when the number of sources exceeds a certain minimum. The locations of the calibrating sources need not be known a priori and need only satisfy mild regularity conditions. A calibration procedure is proposed which uses maximum-likelihood techniques     

Kalman filtering for matrix estimation

A general discrete-time Kalman filter (KF) for state matrix estimation using matrix measurements is presented. The new algorithm evaluates the state matrix estimate and the estimation error covariance matrix in terms of the original system matrices. The proposed algorithm naturally fits systems which are most conveniently described by matrix process and measurement equations. Its formulation uses a compact notation for aiding both intuition and mathematical manipulation. It is a straightforward extension of the classical KF, and includes as special cases other matrix filters that were developed in the past. Beyond the analytical value of the matrix filter, it is shown through various examples arising in engineering problems that this filter can be computationally more efficient than its vectorized version.     

High-power Ka-band TWTs for airborne radars

Litton EDD is developing a new class of Ka-band traveling-wave tubes (TWTs) that use a novel integral-polepiece folded-waveguide circuit to generate peak and average powers up to 1,500 watts. Rugged and highly reliable, this new technology is especially suited for airborne radars. Ongoing developments to increase the average power, the bandwidth and the frequency may be useful for future designs     

An alternate algorithm for discrete-time filtering

The discrete-time Kalman filter is an optimal estimator for the states of a linear, stochastic system. It assumes that measurements are linear combinations of the states, and all disturbances are Gaussian. The influence diagram, a decision analysis tool that provides an algorithm for discrete-time filtering equivalent to the Kalman filter when the influence diagram represents Gaussian random variables, is discussed. The influence diagram algorithm is a factored form of the Kalman filter, similar to other factored forms such as the U-D filter. Compared with the Kalman filter, it offers improved numerical properties. Compared with other factored forms, it offers a reduced computational load     

Digital beamforming calibration for FMCW radar

Three sources of beamforming deterioration are identified for an FMCW radar. These all relate to time-of-arrival and cable delays. There are small range-dependent phase errors at the receiver outputs. The delays cause frequency shifts, which produce phase errors at the discrete Fourier transform (DFT) outputs after ranging. These frequency shifts cause amplitude errors when the signals are resolved into the same range bin. Two methods of compensating for phase and amplitude errors are proposed. The first corrects for phase errors prior to beamforming. Amplitude errors are ignored but the residual error is usually small. The second method aligns the receiver frequencies digitally before ranging. This eliminates the phase errors and the amplitude errors at the DFT range estimates     

Regenerative hybrid arrays for interference suppression

The authors propose two regenerative hybrid adaptive arrays in which a self-generated reference signal is obtained through a detection-modulation procedure from the array output. The proposed arrays do not depend on spectrum spreading and are therefore applicable when this feature is not available. It is shown that at steady state the performance of these regenerative hybrid arrays is approximately the same as that of a hybrid array with a perfect reference signal. As to transient behavior, these arrays are shown to converge if the available imperfect steering vector can result in a few dB output signal-to-interference-plus-noise ratio with the self-generated reference disabled     

Status of CR-like lower bounds for nonlinear filtering

The motivation and mechanics of utilizing Cramer-Rao (CR) -type lower bounds to gauge the performance of filters being evaluated in nonlinear estimation applications such as in sonar, sonobuoy, and radar target tracking are reviewed. The status of several similar alternative CR-type lower bounds that have been considered or used for this purpose and certain limitations and/or caveats associated with their use are offered. These results should be of interest to sonar, sonobuoy, and radar practitioners and Kalman-filtering or nonlinear-filtering theorists     

Convergence analysis for inexact mechanization of Kalman filtering

A computational aspect of real-time estimation is considered, in which the estimation algorithm to be used has the standard optimal Kalman filtering structure, but the actual inverse matrix within the Kalman gain is replaced by an expedient approximation at each instant. In real-time applications, most Kalman filtering schemes are approximate to a degree as a consequence of numerical roundoff matrix inversion. The convergence properties and error estimates of such schemes are obtained to provide a theoretical basis for gauging the utility of using the above approximations of the Kalman gain matrix at each time instant. A new exponentially convergent scheme is also suggested for approximating the inverse matrix within the Kalman gain. Conditions are determined under which online approximate matrix inversion can be eliminated as the cause of Kalman filter divergence in real-time implementations     

Space-time autoregressive filtering for matched subspace STAP

Practical space-time adaptive processing (STAP) implementations rely on reduced-dimension processing, using techniques such as principle components or partially adaptive filters. The dimension reduction not only decreases the computational load, it also reduces the sample support required for estimating the interference statistics. This results because the clutter covariance is implicitly assumed to possess a certain (nonparametric) structure. We demonstrate how imposing a parametric structure on the clutter and jamming can lead to a further reduction in both computation and secondary sample support. Our approach, referred to as space-time autoregressive (STAR) filtering, is applied in two steps: first, a structured subspace orthogonal to that in which the clutter and interference reside is found, and second, a detector matched to this subspace is used to determine whether or not a target is present. Using a realistic simulated data set for circular array STAP, we demonstrate that this approach achieves significantly lower signal-to-interference plus noise ratio (SINR) loss with a computational load that is less than that required by other popular approaches. The STAR algorithm also yields excellent performance with very small secondary sample support, a feature that is particularly attractive for applications involving nonstationary clutter.     

Null phase-shift polarization filtering for high-frequency radar

In order to effectively cancel the interference in polarization filtering, the parameters of the polarization filter should timely adapt to the variation of the polarization of the interference, which may impact the amplitude and phase of the desired signal that passes through the same polarization filter during the coherent integration time (CIT) and render the enhancement of the signal integration a failure. To avoid this, a null phase-shift polarization (NPSP) filter is proposed, which is composed of a linear polarization transformer (LPVT), a conventional single-notch polarization (SNP) filter and an amplitude/phase compensation device (A/PCD). The interference, which has polarization different from those of the desired target signal, can be suppressed completely while the target signal remains without distortion. Some applications of high-frequency (HF) radars for suppressing the radio interference are introduced. Simulation results from the experimentally derived data indicate that the improvement of the signal-to-interference ratio (SIR) can be expected to be more than 28 dB. The proposed NPSP filter is effective in HF radar or other coherent systems.     

Efficient particle filtering for road-constrained target tracking

The variable-structure multiple-model particle filtering approach for state estimation of road-constrained targets is addressed. The multiple models are designed to account for target maneuvers including "move-stop-move" and motion ambiguity at an intersection; the time-varying active model sets are adaptively selected based on target state and local terrain condition. The hybrid state space is partitioned into the mode subspace and the target subspace. The mode state is estimated based on random sampling; the target state as well as the relevant likelihood function associated with a mode sample sequence is approximated as Gaussian distribution, of which the conditional mean and covariance are deterministically computed using a nonlinear Kalman filter which accounts for road constraints in its update. The importance function for the sampling of the mode state approximates the optimal importance function under the same Gaussian assumption of the target state.     

机载电气设备ATE的设计和实现

介绍了电气设备ATE系统的软、硬件设计和实现电气设备ATE是一套总线式机载设备地面自动检测系统,采用开放式ATE系统结构,应用VXI和GPIB总线技术和先进的图形化测试软件技术等.     

Accuracy of using point targets for SAR calibration

The peak and integral methods for radiometric calibration of a synthetic aperture radar (SAR) using reference point targets are analyzed. Both calibration methods are shown to be unbiased, but the peak method requires knowledge of the equivalent rectangle system resolution which is sensitive to system focus. Exact expressions for the RMS errors of both methods are derived. It is shown that the RMS error resulting from the peak method is always smaller than or equal to that from the integral method for a well-focused system. However, for robust radiometric calibration of SAR, or when nonlinear phase errors are present, the integral method is recommended, because it does not require detailed knowledge of the impulse response and the resulting RMS error is not dependent on system focus     

Strategies for in-orbit calibration of drag-free control systems

Drag-Free Satellites (DFS) are a class of scientific satellite missions designed for research on fundamental physics as well as geodesy. They consist, basically, of a small inner satellite (test mass) located in a cavity inside a larger satellite, the normal one. The Drag-Free Attitude Control System (DFACS) is the most complex technology on-board these satellites. This key technology allows the residual accelerations on experiments on board the satellites to be significantly reduced. In order to achieve this very low disturbance environment (for some missions <10⁻¹⁴ g) the drag-free control system has to be optimized. This optimization process is required because of uncertainties in system parameters that demand a robustness of the control system. This paper will present approaches for in-orbit calibration of drag-free control systems. The discussion includes modeling, with scale factors and cross couplings, possible excitation signals, comparison of different parameter identification/estimation methods as well as simulation results.     

Eigenstructure-based algorithms for direction finding withtime-varying arrays

This paper considers the problem of finding the directions of narrowband signals using a time-varying array whose elements move during the observation interval in an arbitrary but known way. We derive two eigenstructure-based algorithms for this problem, which are modifications of techniques developed originally for time-invariant arrays. The first uses array interpolation, and the second uses focusing matrices. Like other eigenstructure-based methods, these algorithms require a modest amount of computations in comparison with the maximum likelihood (ML) estimator. The performance of the algorithms is evaluated by Monte-Carlo simulations, and is compared with the Cramer Rao Bound (CRB). Although both techniques were successful for wideband array processing with time-invariant arrays, we found that only the interpolated array algorithm is useful for direction finding (DF) with time-varying arrays     

Coherent spatial filtering for SAR detection of stationary targets

Analysis of UHF synthetic aperture radar (SAR) images has revealed a spatially correlated phase structure over a resolved target such as a long wire or a large truck. This phase variation, approximated by a simple, range-dependent factor 4πr/λ, results in a line-shaped image spatial spectrum. Such image phase and spectral features can be exploited by coherent spatial filtering to improve target-to-clutter ratios of large targets and stationary target detectability in a strong clutter environment     

Development of airborne moving target radar for long range surveillance

The following topics are discussed in the context of the development of an airborne moving target radar for long range surveillance: US Navy long range shipborne radar; Cadillac I airborne early warning (AEW) radar; Cadillac II airborne early warning (AEW) radar; airborne moving target indicating (AMTI) radar; related post-war radar activities; and the invention of the displaced center antenna. Among the topics studied is the use of a monopulse antenna in an MTI radar to remove the degradation of the MTI caused by rapid scanning of the antenna. A method of using a monopulse antenna for motion compensation in airborne MTI is discussed.<>     

Multiple moving target feature extraction for airborne HRR radar

This study considers the clutter suppression and feature extraction of multiple moving targets for airborne high range resolution (HRR) phased array radar. To avoid the range migration problems that occur in the HRR radar data, we divide each HRR profile into nonoverlapping low range resolution segments. No information is lost due to the division and hence no loss of resolution occurs. We show how to use a vector auto-regressive filtering technique to suppress the clutter. Then a relaxation-based parameter estimation algorithm is presented for multiple moving target feature extraction. Numerical results are given to demonstrate the effectiveness of the algorithm     

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.