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.     

Remote data sensing using SAR and harmonic reradiators

In sensor networks distributed over large areas, communication by means of active transmitters on sensor nodes is inherently energy expensive and poses a significant bottleneck to achieve a long battery life. We propose modulated reradiation of radar illumination as a means to transmit information from a group of sensors to an airborne radar. This puts the communications energy burden on the radar transmitter rather than on the sensor nodes, thus increasing their battery lifetimes. To distinguish the sensor return from the clutter return, the modulation on the sensors is done by switching a nonlinear load on the sensor antenna and processing the harmonic reradiation. We present techniques to transmit information from the sensors, which use stripmap mode synthetic aperture radar (SAR) ideas to decode the information and to simultaneously obtain a geographic map of the sensor locations.     

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     

Steady-state analysis of the constant-frequency clamped seriesresonant converter

A constant-frequency diode-clamped series resonant converter (CFCSRC) is proposed as a solution to problems associated with frequency-controlled resonant converters. This converter has two resonant frequencies, and control is achieved by varying the relative time spent at each switching frequency. Two zero-current-switching (ZCS) modes are examined and plotted in the output plane. An equation is given for the boundary between the two ZCS modes, as well as an expression for the boundary between ZCS and non-ZCS operation; both are plotted in the output plane. The output equation for the main mode is shown to be hyperbolic. Converter peak voltages limited to the input voltages, and peak currents are less than those of the frequency-controlled clamped series resonant converter over a large operating range. Data from a prototype converter are compared with theoretical data and are shown to be in good agreement with the theoretical model     

A recursive multiple model approach to noise identification

Correct knowledge of noise statistics is essential for an estimator or controller to have reliable performance. In practice, however, the noise statistics are unknown or not known perfectly and thus need to be identified. Previous work on noise identification is limited to stationary noise and noise with slowly varying statistics only. An approach is presented here that is valid for nonstationary noise with rapidly or slowly varying statistics as well as stationary noise. This approach is based on the estimation with multiple hybrid system models. As one of the most cost-effective estimation schemes for hybrid system, the interacting multiple model (IMM) algorithm is used in this approach. The IMM algorithm has two desirable properties: it is recursive and has fixed computational requirements per cycle. The proposed approach is evaluated via a number of representative examples by both Monte Carlo simulations and a nonsimulation technique of performance prediction developed by the authors recently. The application of the proposed approach to failure detection is also illustrated     

A localizer design to improve missed approach guidance

A novel VHF localizer system has been designed, built and successfully tested to provide increased reliability and safety of commercial and general aviation air transportation. Additional benefits are more precise tracks for aircraft executing a missed approach, reduced volume of the airspace needed for missed approaches, and reduced sizes of areas affected by noise. The design uses contemporary instrument landing system (ILS) hardware to provide dual independent front and back course directional localizer operation with two carriers in the receiver passband offset 4 kHz from the nominal carrier frequency. An example is given of an application and solution to an ILS problem at Reno, NV. Relevant data are presented     

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     

Light scattering in planetary atmospheres

This paper reviews scattering theory required for analysis of light reflected by planetary atmospheres. Section 1 defines the radiative quantities which are observed. Section 2 demonstrates the dependence of single-scattered radiation on the physical properties of the scatterers. Section 3 describes several methods to compute the effects of multiple scattering on the reflected light.     

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.