Track-While-Scan Algorithm in a Clutter Environment

A track-while scan (TWS) algorithm is developed for targets in a clutter environment. The problem has been studied using only the position measurements [1, 5-8], but the simulation results have not been satisfactory. Modern processing techniques (FFT processor) ) in air traffic control and surveillance radar receivers provide both position and radial velocity. The radial velocity measurement may be conveniently used in the target-track correlation process, which will reduce the association ambiguity in the clutter environment. t. In the clear environment the algorithm using the position and radial velocity measurements has been treated in [3, 4]. A TWS algorithm, using both position and radial velocity measurements for targets in a clutter environment, is presented here. The algorithm obtained is nonlinear and adaptive. In order to evaluate the improvement due to radial velocity measurement a simulation has been performed on a digital computer. The algorithm was run with and without radial velocity measurements to compare its performances. An improvement was noted especially when the target path included an accelerated portion.     

The Tactical Communications Satellite

Early in 1969 the U. S. Air Force placed into synchronous orbit the largest communications satellite built to date. This vehicle, the tactical communications satellite (TACSAT), together with a variety of ground terminals, is designed to test experimentally and develop tactical communications concepts for all military services. This paper describes the spacecraft design focusing on the communications repeater. Measured performance characteristics affecting communications utilization of the spacecraft are presented.     

A Detection Algorithm for Optical Targets in Clutter

There is active interest in the development of algorithms for detecting weak stationary optical and IR targets in a heavy opticalclutter background. Often only poor detectability of low signal-to-noise ratio (SNR) targets is achieved when the direct correlation method is used. In many cases, this is partly obviated by using detection with correlated reference scenes [1, 2].This paper uses the experimentally justified assumption that most optical clutter can be modeled as a whitened Gaussian randomprocess with a rapidly space-varying mean and a more slowlyvarying covariance [2]. With this assumption, a new constant falsealarm rate (CFAR) detector is developed as an application of the classical generalized maximum likelihood ratio test of Neyman and Pearson. The final CFAR test is a dimensionless ratio. This test exhibits the desirable property that its probability of a false alarm(PFA) is independent of the covariance matrix of the actual noiseencountered. When the underlying noise processes are complex intime, similar considerations can yield a sidelobe canceler CFARdetection criterion for radar and communications. Performance analyses based on the probability of detection (PD)versus signal-to-noise ratio for several given fixed false alarm probabilities are presented. Finally these performance curves are validated by computer simulations of the detection process which use real image data with artificially implanted signals.     

Model-based segmentation of FLIR images

The use of gray-scale intensities together with the edge information present in a forward-looking infrared (FLIR) image to obtain a precise and accurate segmentation of a target is presented. A model of FLIR images based on gray-scale and edge information is incorporated in a gradient relaxation technique which explicitly maximizes a criterion function based on the inconsistency and ambiguity of classification of pixels with respect to their neighbors. Four variations of the basic technique which provide automatic selection of thresholds to segment FLIR images are considered. These methods are compared, and several examples of segmentation of ship images are given     

Efficient algorithms for finding the K best paths througha trellis

A set of algorithms is presented for finding the best set of K mutually exclusive paths through a trellis of N nodes, with worst-case computation time bounded by N³log n for a fixed-precision computation. The algorithms are based on a transformation of the K-path trellis problem into an equivalent minimum-cost network flow (MCNF) problem. The approach allows the application of efficient MCNF algorithms, which can obtain optimal solutions orders of magnitude faster than the algorithm proposed by J.K. Wolf et al. (1989). The resulting algorithms extend the practicality of the trellis formulation (in terms of required computations) to multiobject tracking problems with much larger numbers of targets and false alarms. A response by Wolf et al. is included     

Filtering of discontinuous processes arising in marine integratednavigation systems

A refined stochastic model for the errors of the Loran-C radio navigation aid is described, and it is shown how this model can be used to improve the performance of integrated navigation systems. In addition to the usual propagation errors, Loran-C time of arrival measurements are occasionally plagued with sudden intermittent errors of a particular magnitude and caused by receiver cycle selection errors. These result in sudden large jumps in the calculated position solution. The Loran-C error has been modeled as the sum of a diffusion process, representing the normal propagating errors, and a pure jump process of Poisson type, representing the cycle selection errors. A simple integrated navigation system is then described, based on the Loran-C model and the standard dead reckoning (heading and speed) system model. Assuming that the observed process is governed by a linear stochastic difference equation, a recursive linear unbiased minimum variance filter is developed, from which the Loran-C and dead reckoning errors, and hence position and velocity, can be estimated     

Gravitation and celestial mechanics investigations with Galileo

The gravitation and celestial mechanics investigations during the cruise phase and Orbiter phase of the Galileo mission depend on Doppler and ranging measurements generated by the Deep Space Network (DSN) at its three spacecraft tracking sites in California, Australia, and Spain. Other investigations which also rely on DSN data, and which like ours fall under the general discipline of spacecraft radio science, are described in a companion paper by Howard et al. (1992). We group our investigations into four broad categories as follows: (1) the determination of the gravity fields of Jupiter and its four major satellites during the orbital tour, (2) a search for gravitational radiation as evidenced by perturbations to the coherent Doppler link between the spacecraft and Earth, (3) the mathematical modeling, and by implication tests, of general relativistic effects on the Doppler and ranging data during both cruise and orbiter phases, and (4) an improvement in the ephemeris of Jupiter by means of spacecraft ranging during the Orbiter phase. The gravity fields are accessible because of their effects on the spacecraft motion, determined primarily from the Doppler data. For the Galilean satellites we will determine second degree and order gravity harmonics that will yield new information on the central condensation and likely composition of material within these giant satellites (Hubbard and Anderson, 1978). The search for gravitational radiation is being conducted in cruise for periods of 40 days centered around solar opposition. During these times the radio link is least affected by scintillations introduced by solar plasma. Our sensitivity to the amplitude of sinusoidal signals approaches 10^-15 in a band of gravitational frequencies between 10^-4 and 10^-3 Hz, by far the best sensitivity obtained in this band to date. In addition to the primary objectives of our investigations, we discuss two secondary objectives: the determination of a range fix on Venus during the flyby on 10 February, 1990, and the determination of the Earth's mass (GM) from the two Earth gravity assists, EGA1 in December 1990 and EGA2 in December 1992.     

Detection in correlated Gaussian plus impulsive noise

A detector which is designed to operate in a correlated Gaussian-plus-impulsive-noise environment is presented. The detector whitens the data robustly and then uses a two-sided threshold test to determine the presence of impulsive samples. The impulsive samples are discarded, and the remaining samples are used to detect the presence or absence of a signal using a matched filter. An approximate analysis is presented, and simulations are used to demonstrate the effectiveness of this approach     

Single-phase power distribution system power flow and faultanalysis

Alternative methods for power flow and fault analysis of single-phase distribution systems are presented. The algorithms for both power flow and fault analysis utilize a generalized approach to network modeling. The generalized admittance matrix, formed using elements of linear graph theory, is an accurate network model for all possible single-phase network configurations. Unlike the standard nodal admittance matrix formulation algorithms, the generalized approach uses generalized component models for the transmission line and transformer. The standard assumption of a common node voltage reference point is not required to construct the generalized admittance matrix. Therefore, truly accurate simulation results can be obtained for networks that cannot be modeled using traditional techniques