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     

Observer-type Kalman innovation filter for uncertain linear systems

An observer-type of Kalman innovation filtering algorithm to find a practically implementable "best" Kalman filter, and such an algorithm based on the evolutionary programming (EP) optima-search technique, are proposed, for linear discrete-time systems with time-invariant unknown-but-hounded plant and noise uncertainties. The worst-case parameter set from the stochastic uncertain system represented by the interval form with respect to the implemented "best" filter is also found in this work for demonstrating the effectiveness of the proposed filtering scheme. The new EP-based algorithm utilizes the global optima-searching capability of EP to find the optimal Kalman filter and state estimates at every iteration, which include both the best possible worst case Interval and the optimal nominal trajectory of the Kalman filtering estimates of the system state vectors. Simulation results are included to show that the new algorithm yields more accurate estimates and is less conservative as compared with other related robust filtering schemes     

Discrete-time min-max tracking

The problem of optimal state estimation of linear discrete-time systems with measured outputs that are corrupted by additive white noise is addressed. Such estimation is often encountered in problems of target tracking where the target dynamics is driven by finite energy signals, whereas the measurement noise is approximated by white noise. The relevant cost function for such tracking problems is the expected value of the standard H/sub /spl infin// performance index, with respect to the measurement noise statistics. The estimator, serving as a tracking filter, tries to minimize the mean-square estimation error, and the exogenous disturbance, which may represent the target maneuvers, tries to maximize this error while being penalized for its energy. The solution, which is obtained by completing the cost function to squares, is shown to satisfy also the matrix version of the maximum principle. The solution is derived in terms of two coupled Riccati difference equations from which the filter gains are derived. In the case where an infinite penalty is imposed on the energy of the exogenous disturbance, the celebrated discrete-time Kalman filter is recovered. A local iterations scheme which is based on linear matrix inequalities is proposed to solve these equations. An illustrative example is given where the velocity of a maneuvering target has to be estimated utilizing noisy measurements of the target position.     

Forecasting the 23 and 24 solar cycles on the basis of MGM spectrum

A new method of nonlinear spectral analysis (called the method of global minimum: MGM), based on the best presentation (in sense of minimal squares) of a given time data set as a sum of sinusoids whose frequencies, amplitudes and phases are to be determined, has been used to find periodicities in annual Wolf sunspot numbers (W) during the period 1700–1995. The possible future behaviour of the 11-year solar cycle (based on an extrapolation of the calculated model) is also presented. The main characteristics of the 23^rd solar cycle are as follows: the W maximum occurs about 2004, with a peak of nearly 220. An unusually large value of W will occur during the 23^rd cycle, which should be characterised by the longest maximum, specifically, W will be greater than 100 during the 11-year period from 1997 to 2007. The first sharp rise will occur during the period 1996–1998, the second sharp during 2002–2004. The main features of the 24 year cycle are as follows: the next minimum in W, associated with the 24^th solar cycle, should occur in the year 2008 and the maximum in 2014. W is expected to peak at about 180. The minimum value for the 25^th year cycle is expected to occur in the year 2019. It is shown that the accuracy of these predictions depends, first of all, on the extrapolation of the hyperlong harmonic of the calculated polyharmonic model fit of observed annual sunspot numbers during the period 1700–1995. The error bars in the definition of the maximum and minimum epochs can be as large as two years.     

Attractive manifold-based adaptive solar attitude control of satellites in elliptic orbits

The paper presents a novel noncertainty-equivalent adaptive (NCEA) control system for the pitch attitude control of satellites in elliptic orbits using solar radiation pressure (SRP). The satellite is equipped with two identical solar flaps to produce control moments. The adaptive law is based on the attractive manifold design using filtered signals for synthesis, which is a modification of the immersion and invariance (I&I) method. The control system has a modular controller–estimator structure and has separate tunable gains. A special feature of this NCEA law is that the trajectories of the satellite converge to a manifold in an extended state space, and the adaptive law recovers the performance of a deterministic controller. This recovery of performance cannot be obtained with certainty-equivalent adaptive (CEA) laws. Simulation results are presented which show that the NCEA law accomplishes precise attitude control of the satellite in an elliptic orbit, despite large parameter uncertainties.     

High resolution radar clutter statistics

The generalized compound probability density function (GC-pdf) is presented for modeling high resolution radar clutter. In particular, the model is used to describe deviation of the speckle component from the Rayleigh to Weibull or other pdfs with longer tails. The GC-pdf is formed using the generalized gamma (GΓ) pdf to describe both the speckle and the modulation component of the radar clutter. The proposed model is analyzed and thermal noise is incorporated into it. The validation of the GC-pdf with real data is carried out employing the statistical moments as well as goodness-of-fit tests. A large variety of experimental data is used for this purpose. The GC-pdf outperforms the K-pdf in modeling high resolution radar clutter and reveals its structural characteristics     

History of monopulse radar in the USSR

Monopulse radars have played an important role in air and missile defense systems since the development of the monopulse technique in the late 1940s. This paper outlines the application of monopulse radars in Russian defense systems, starting with the Moscow ABM system and continuing in instrumentation and air defense radars now widely deployed in Russia and elsewhere     

Longitudinal Waves in Coronal Loops

Outwardly propagating intensity disturbances are a common feature in large, quiescent coronal loop structures. In this paper, an overview is given of the observed properties and the theoretical modelling. As a large number of events have been observed and analysed, good statistical results on the estimated parameters have now been obtained. The theoretical modelling mainly focuses on two distinct aspects, namely the observed rapid damping of the perturbations, thought to be due to thermal conduction and the origin of the driver. Leakage of the solar surface p-modes is the main candidate to explain the observed periodicity, due to the strong correlation between loop position and period and the filamentary nature of the observed coronal intensity perturbations. Recent observational results appear to confirm the leakage and subsequent upward propagation of the solar surface 5 minute oscillations into the overlying atmospheric layers.