Adaptive cancellation method for geometry-induced nonstationary bistatic clutter environments

This paper describes and characterizes a new bistatic space-time adaptive processing (STAP) clutter mitigation method. The approach involves estimating and compensating aspects of the spatially varying bistatic clutter response in both angle and Doppler prior to adaptive clutter suppression. An important feature of the proposed method is its ability to extract requisite implementation information from the data itself, rather than rely on ancillary - and possibly erroneous or missing - system measurements. We justify the essence of the proposed method by showing its ability to align the dominant clutter subspaces of each range realization relative to a suitably chosen reference point as a means of homogenizing the space-time data set. Moreover, we numerically characterize performance using synthetic bistatic clutter data. For the examples considered herein, the proposed bistatic STAP method leads to maximum performance improvements between 17.25 dB and 20.75 dB relative to traditional STAP application, with average improvements of 6 dB to 10 dB.     

Search radar detection and track with the Hough transform. II.detection statistics

For pt.I see ibid., vol.30, no.1, (Jan.1994). This paper describes the calculation of P_F and P_D for the Hough transform technique when the primary threshold crossings are weighted by their power before transforming (i.e., noncoherent integration). After expressions for P_F and P_D are derived, we examine the question of optimal granularity of the Hough accumulator space. We also investigate the relationship between primary and secondary thresholds and its effect on detectability     

Multiple target tracking using products of position measurements

The continued development of the symmetric measurement equation (SME) filter for track maintenance in multiple target tracking (MTT) is considered, focusing on the case in which the SMEs are generated by forming sums of products of the original position measurements. The SME filter is developed for the case of N targets whose motions consist of random perturbations about constant-velocity trajectories. It is assumed that measurements of x-coordinate positions are available, and that the number of measurements is equal to the number of targets. Various analytical properties of the SME filter are studied. It is shown that under a very weak condition, the estimation error equation is locally exponentially stable. The performance of the SME filter is investigated by comparing it with an optimal (minimum-variance) estimator and by generating a computer simulation in the six-target case     

Speech Data Rate Reduction Part II: Applicability of Sensitivity and Error Analysis

This paper deals with the application of modern estimation techniques to the problem of speech data rate reduction. It is desirable to adaptively identify and quantitize the parameters of the speech model. These paramaters cannot be identified and quantized exactly; the performance of the predictor is thereby degraded and this could prevent data reduction. In many cases it is desirable to emply a suboptimal predictor in order to simplify the algorithms, and predictor performance is again degraded. This paper develops sensitivity and error analysis as a potential method for determining quantitatively how speech data reduction system performance is degraded by imprecise parameter knowledge or suboptimal filtering. An intended use of the sensitivity and error analysis algorithms is to determine parameter identification and model structure requirements of configuration concepts for adaptive speech digitizers. First, sensitivity and error analysis algorithms are presented that form the basis for the remainder of the work. The algorithms are then used to determine how imprecise knowledge of vocal tract parameters degrades predictor performance in speech. Transversal filters have previously been proposed for this application. The sensitivity analysis algorithms are then used to determine when and by how much the transverse filter is suboptimal to the Kalman filter. In particular, the question of how effectively a higher order of all-pole model approximates a system with zeros is answered, as this question is of considerable importance in speech. Finally, the physical significance of the innovations process in speech data rate reduction is studied.     

Langmuir Turbulence and Solar Radio Bursts

Langmuir waves and turbulence resulting from an electron beam-plasma instability play a fundamental role in the generation of solar radio bursts. We report recent theoretical advances in nonlinear dynamics of Langmuir waves. First, starting from the generalized Zakharov equations, we study the parametric excitation of solar radio bursts at the fundamental plasma frequency driven by a pair of oppositely propagating Langmuir waves with different wave amplitudes. Next, we briefly discuss the emergence of chaos in the Zakharov equations. We point out that chaos can lead to turbulence in the source regions of solar radio emissions. This revised version was published online in August 2006 with corrections to the Cover Date.     

Blind adaptive decision fusion for distributed detection

We consider the problem of decision fusion in a distributed detection system. In this system, each detector makes a binary decision based on its own observation, and then communicates its binary decision to a fusion center. The objective of the fusion center is to optimally fuse the local decisions in order to minimize the final error probability. To implement such an optimal fusion center, the performance parameters of each detector (i.e., its probabilities of false alarm and missed detection) as well as the a priori probabilities of the hypotheses must be known. However, in practical applications these statistics may be unknown or may vary with time. We develop a recursive algorithm that approximates these unknown values on-line. We then use these approximations to adapt the fusion center. Our algorithm is based on an explicit analytic relation between the unknown probabilities and the joint probabilities of the local decisions. Under the assumption that the local observations are conditionally independent, the estimates given by our algorithm are shown to be asymptotically unbiased and converge to their true values at the rate of O(1/k/sup 1/2/) in the rms error sense, where k is the number of iterations. Simulation results indicate that our algorithm is substantially more reliable than two existing (asymptotically biased) algorithms, and performs at least as well as those algorithms when they work.     

Solar wind corotating stream interaction regions out of the ecliptic plane: Ulysses

Ulysses plasma observations reveal that the forward shocks that commonly bound the leading edges of corotating interaction regions (CIRs) beyond 2 AU from the Sun at low heliographic latitudes nearly disappeared at a latitude of S26°. On the other hand, the reverse shocks that commonly bound the trailing edges of the CIRs were observed regularly up to S41.5°, but became weaker with increasing latitude. Only three CIR shocks have been observed poleward of S41.5°; all of these were weak reverse shocks. The above effects are a result of the forward waves propagating to lower heliographic latitudes and the reverse waves to higher latitudes with increasing heliocentric distance. These observational results are in excellent agreement with the predictions of a global model of solar wind flows that originate in a simple tilted-dipole geometry back at the Sun.     

The Plasma Environment of Comet 67P/Churyumov-Gerasimenko Throughout the Rosetta Main Mission

The plasma environment of comet 67P/Churyumov-Gerasimenko, the Rosetta mission target comet, is explored over a range of heliocentric distances throughout the mission: 3.25 AU (Rosetta instruments on), 2.7 AU (Lander down), 2.0 AU, and 1.3 AU (perihelion). Because of the large range of gas production rates, we have used both a fluid-based magnetohydrodynamic (MHD) model as well as a semi-kinetic hybrid particle model to study the plasma distribution. We describe the variation in plasma environs over the mission as well as the differences between the two modeling approaches under different conditions. In addition, we present results from a field aligned, two-stream transport electron model of the suprathermal electron flux when the comet is near perihelion.     

Problems with the concept of the inflationary universe

The picture of an exponentially increasing, “inflationary” phase of the early universe (Guth 1981; Linde 1982; Albrecht and Steinhardt 1982) may point the way to an understanding of our present universe without reference to extremely specific initial conditions. The model rests, however, on several assumptions which deserve critical examination.