Frequency estimation techniques for high dynamic trajectories

A comparison is presented of four different estimation techniques applied to the problem of continuously estimating the rapidly varying parameters of a sinusoidal signal, observed in the presence of additive noise. Frequency estimates are emphasized, although phase and/or frequency rate are also estimated by some of the algorithms. These parameters are related to the velocity, position, and acceleration of the maneuvering receiver or transmitter. Estimated performance at low carrier-to-noise ratios and high dynamics is investigated for the purpose of determining the useful operating range of an approximate maximum likelihood estimator, an extended Kalman filter, a cross-product automatic frequency loop and a phase-locked loop. Numerical simulations are used to evaluate performance while tracking a common trajectory exhibiting high dynamics     

An exact expression for resolution cell area in special case ofbistatic radar systems

An exact expression for the bistatic resolution-cell area (A _B) is developed for the special case in which either the transmit or receive antenna has a broad azimuth beamwidth or is omnidirectional. Quantitative examples are presented to illustrate the variation of A_B with location. A comparison is made with the performance of a commonly used approximation formula     

Detection performance in K-distributed and correlatedRayleigh clutters

Performance prediction for a detection system employing noncoherent integration is carried out for a chi-square family of fluctuating targets in K-distributed clutter plus noise. The detection performance for Swerling 11 targets in the K-distributed clutter plus noise is compared with that in exponentially correlated Rayleigh clutter. The results show that the performance prediction based on N pulses integrated in clutter plus noise using the K-distributed clutter model may be approximately equivalent to that using the exponentially correlated Rayleigh-distributed clutter model     

Multisensor tracking of a maneuvering target in clutter

An algorithm is presented for tracking a highly maneuvering target using two different sensors, a radar and an infrared sensor, assumed to operate in a cluttered environment. The nonparametric probabilist data association filter (PDAF) has been adapted for the multisensor (MS) case, yielding the MSPDAF. To accommodate the fact that the target can be highly maneuvering, the interacting multiple model (IMM) approach is used. The results of single-model-based filters and of the IMM/MSPDAF algorithm with two and three models are presented and compared. The IMM has been shown to be able to adapt itself to the type of motion exhibited by the target in the presence of heavy clutter. It yielded high accuracy in the absence of acceleration and kept the target in track during the high acceleration periods     

A gentle process for the formation of Algols

This work is concerned with binary systems that we call ‘moderately close’. These are systems in which the primary (by which we mean the initially more massive star) fills its Roche lobe when it is on the giant branch with a deep convective envelope but before helium ignition (late case B). We find that if the mass ratio q(= M ₁/M ₂) < q _crit = 0.7 when the primary fills its Roche lobe positive feedback will lead to a rapid hydrodynamic phase of mass transfer which will probably lead to common envelope evolution and thence to either coalescence or possibly to a close binary in a planetary nebula. Although most Algols have probably filled their Roche lobes before evolving off the main-sequence we find that some could not have and are therefore ‘moderately close’. Since rapid overflow is unlikely to lead to an Algol-like system there must be some way of avoiding it. The most likely possibility is that the primary can lose sufficient mass to reduce q below q _crit before overflow begins. Ordinary mass loss rates are insufficient but evidence that enhanced mass loss does take place is provided by RS CVn systems that have inverted mass ratios but have not yet begun mass transfer. We postulate that the cause of enhanced mass loss lies in the heating of the corona by by magnetic fields maintained by an α — ω dynamo which is enhanced by tidal effects associated with corotation. In order to model the the effects of enhanced mass loss we ignore the details and adopt an empirical approach calibrating a simple formula with the RS CVn system Z Her. Using further empirical relations (deduced from detailed stellar models) that describe the evolution of red giants we have investigated the effect on a large number of systems of various initial mass ratios and periods. These are notable in that some systems can now enter a much gentler Algol-like overflow phase and others are prevented from transferring mass altogether. We have also investigated the effects of enhanced angular momentum loss induced by corotation of the wind in the strong magnetic fields and consider this in relation to observed period changes. We find that a typical ‘moderately close’ Algol-like system evolves through an RS CVn like system and then possibly a symbiotic state before becoming an Algol and then goes on through a red giant-white dwarf state which may become symbiotic before ending up as a double white dwarf system in either a close or wide orbit depending on how much mass is lost before the secondary fills its Roche lobe.     

ARMA Time Series Modeling: an Effective Method

The ability to generate rational models of time series plays an important role in such applications as adaptive filtering, spectral estimation, digital control, array processing, and forecasting. A method for effecting an autoregressive moving average (ARMA) model estimate is presented which possesses a number of admirable properties: 1) it has an elegant algebraic structure, 2) its modeling performance in spectral estimation applications has been empirically found to typically exceed that of such contemporary techniques as the periodogram, the Burg method, and the Box-Jenkins method on a variety of problems, 3) it is implementable by computationally efficient algorithms, and 4) it is based on pseudomaximum likelihood concepts. Taken in combination, these properties mark this method as being an effective tool in challenging applications requiring high modeling performance in a real time setting.     

Test Results with an Experimental Direction-Finding System

A direction-finding system was built that can simultaneously estimate the arrival angles of two incident signals. It is conceptually straightforward to extend the system to cases with greater numbers of signals. The system is designed to work with uncorrelated signals whose form is unknown, e.g., two communications signals residing in the same bandwidth. Pulsed as well as continuous signals can be handled. The technique involves the determination of the received signal's correlation matrix as an intermediate step. Pattern range tests were performed to determine angle estimate bias and accuracy.     

Investigations of Stability & Dynamic Performances of a Current-Injected Regulator

The stability and dynamic performances of a buck/boost regulator employing a current-injected control are examined. Small-signal models for the power state, the multiloop error processor, and the duty-cycle pulse modulator are developed. The error-processor model which incorporates the current-injected loop, the dc loop, and the compensation network permits evaluation of the effects of each individual control loop and their combined efforts toward shaping the performance characteristics of the closed-loop system. Comparisons are made between this modeling approach and earlier approaches. Some important yet subtle dissimilarities are discussed. This model predicts the constant-frequency 50-percent duty-cycle instability which is inherent to the current-injected control.