Unknown Initial Phase Research Articles

A Bayesian Classifier for X-Ray Pulsars Recognition

Recognition for X-ray pulsars is important for the problem of spacecraft’s attitude determination by X-ray Pulsar Navigation (XPNAV). By using the nonhomogeneous Poisson model of the received photons and the minimum recognition error criterion, a classifier based on the Bayesian theorem is proposed. For X-ray pulsars recognition with unknown Doppler frequency and initial phase, the features of every X-ray pulsar are extracted and the unknown parameters are estimated using the Maximum Likelihood (ML) method. Besides that, a method to recognize unknown X-ray pulsars or X-ray disturbances is proposed. Simulation results certificate the validity of the proposed Bayesian classifier.

Determining the Number of Radio Signals with Unknown Phases

We have carried out the synthesis and analysis of the maximum likelihood and quasi-likelihood algorithms in order to determine the number of radio signals, introducing and calculating the abridged probability of error in the assessment of the number of signals as the quantitative characteristic for the performance evaluation of these algorithms. The achieved analytical results lead us to the comparison between the characteristics of maximum likelihood and quasi-likelihood algorithms in determining the number of signals. We also consider the possibility for the application of the quasi-likelihood algorithm for the determination of the number of radio signals with partially unknown initial phases.

Detection of Radio Signals with Unknown Duration, Amplitude, and Initial Phase

We develop the maximum-likelihood algorithm for detecting a radio signal with an arbitrary envelope shape, which is observed against the background of additive Gaussian white noise. The signal duration, amplitude, and initial phase are unknown. The developed algorithm is analyzed on the assumption of sufficiently large signal-to-noise ratios. Asymptotic expressions for the detection-error probabilities are obtained. The developed-algorithm efficiency is checked by computer simulation and the applicability range of the obtained asymptotic expressions for the algorithm characteristics is determined.

Detection of gravitational radiation from supermassive black hole binaries via pulsar timing

We consider the problem of detection of long-wave gravitational radiation via irregularities in the time of arrival (TOA) of electromagnetic pulsar pulses. As a GW signal model, the gravitational radiation generated by a black hole binary was taken. In the Bayesian approach, a modified algorithm of timing residuals processing is proposed. It is associated with averaging of the likelihood ratio over the unknown initial phase of the binary system. Data processing of the real pulsar timing array has been performed to detect the GW radiation from supermassive black hole binaries located at the centers of the galaxies NGC4151 and OJ287. The upper limit on GW strain amplitude of these sources has been set. Ways of decreasing this limit up to an astrophysically significant level are discussed.

Amplitude estimate of the radio signal with unknown duration and initial phase

Quasi-likelihood and maximum likelihood estimate algorithms of the amplitude of a radio signal with free-form envelope and unknown duration and initial phase are synthesized. Characteristics of the synthesized algorithms are found. The comparison of the accuracy of amplitude estimates is carried out.

Digital compensation of the analog-digital highway nonlinearity in a case of unknown initial phase of the test signal

Digital compensation of the analog-digital highway nonlinearity in a case of unknown initial phase of the test signal

Methods of increasing the speed and accuracy characteristics of converters of orthogonal components of a signal into amplitude

A comparative analysis is made of methods and algorithms for calculating the functions f(x) = x 1/2 and f(x) = 1/x 1/2 from the standpoint of obtaining optimal ratios with respect to conversion time, accuracy characteristics, and software and hardware costs, for the example of measuring the vibration parameters of shafts and the amplitude of signals with an unknown initial phase.

Embryonic assembly of auditory circuits: spiral ganglion and brainstem

During early development, peripheral sensory systems generate physiological activity prior to exposure to normal environmental stimuli. This activity is thought to facilitate maturation of these neurons and their connections, perhaps even promoting efficacy or modifying downstream circuitry. In the mammalian auditory system, initial connections form at embryonic ages, but the functional characteristics of these early neural connections have not been assayed. We investigated processes of embryonic auditory development using a whole-head slice preparation that preserved connectivity between peripheral and brainstem stations of the auditory pathway. Transgenic mice expressing fluorescent protein provided observation of spiral ganglion and cochlear nucleus neurons to facilitate targeted electrophysiological recording. Here we demonstrate an apparent peripheral-to-central order for circuit maturation. Spiral ganglion cells acquire action potential-generating capacity at embryonic day 14 (E14), the earliest age tested, and action potential waveforms begin to mature in advance of comparable states for neurons of the ventral cochlear nucleus (VCN) and medial nucleus of the trapezoid body (MNTB). In accordance, auditory nerve synapses in the VCN are functional at E15, prior to VCN connectivity with the MNTB, which occurs at least 1 day later. Spiral ganglion neurons exhibit spontaneous activity at least by E14 and are able to drive third-order auditory brainstem neurons by E17. This activity precedes cochlear-generated wave activity by 4 days and ear canal opening by at least 2 weeks. Together, these findings reveal a previously unknown initial developmental phase for auditory maturation, and further implicate the spiral ganglion as a potential controlling centre in this process.

Performance Study of Algorithms for Detecting Pulsed Sinusoidal Interference in Microwave Radiometry

The performance of four algorithms for detecting the presence of pulsed sinusoidal interference in microwave radiometry is compared. The pulsed sinusoidal interference sources considered have unknown frequency, initial phase, amplitude, arrival time, and duration. The statistical properties of three of the algorithms are determined analytically, although numerical integrations are required in some cases in order to compute the obtained probabilities of detection. The performance of the fourth algorithm is evaluated using Monte Carlo procedures. Results show that three of the algorithms have a performance that is roughly comparable for the cases considered, while the fourth yields reduced sensitivity. A more detailed study of two of the algorithms, a simple energy detector called the pulse detection algorithm and a ldquopeakrdquo picking detector based on the use of data spectrograms, is also provided.

An Integrated Navigation System Using GPS Carrier Phase for Real-Time Airborne/Synthetic Aperture Radar (SAR)

A Synthetic Aperture Radar (SAR) requires accu- rate measurement of the motion of the imaging plat- form to produce well-focused images with minimal absolute position error. The motion measurement (MoMeas) system consists of a inertial measurement unit (IMU) and a P-code GPS receiver that outputs corrected ephemeris, L1 & L2 pseudoranges, and L1 & L2 carrier phase measurements. The unknown initial carrier phase biases to the GPS satellites are modeled as states in an extended Kalman filter and the resulting integrated navigation solution has po- sition errors that change slowly with time. Position error drifts less than 1- cm/sec have been measured from the SAR imagery for various length apertures.

Estimation of chirp radar signals in compound-Gaussian clutter: a cyclostationary approach

Signal detection of known (within a complex scaling) rank one waveforms in non-Gaussian distributed clutter has received considerable attention. We expand on published solutions to consider the case of rank one waveforms that have some unknown parameters, i.e., signal amplitude, initial phase, Doppler shift, and Doppler rate of change. The contribution of this paper is the derivation and performance analysis of two joint estimators of Doppler shift and Doppler rate-the chirp embedded in correlated compound-Gaussian clutter. One solution is based on the maximum likelihood (ML) principle and the other one on target signal second-order cyclostationarity. The hybrid Cramer-Rao lower bounds (HCRLBs) and a large sample closed-form expression for the mean square estimation error (only for the Doppler shift) are also derived. Numerical examples are provided to show the behavior of the proposed estimator under different non-Gaussian clutter scenarios.

Smooth Output-Feedback Adaptive Compensator of External Disturbances for Nonlinear Systems

In this paper, we propose a smooth adaptive compensator for an external inaccessible disturbance which may be presented as a finite sum of sinusoids of unknown frequencies, magnitudes and initial phases. The disturbance acts in the span of control and the plant is assumed to be an exponentially passive nonlinear system. Under these assumptions it is shown how to design an adaptive compensator which does not depend on the parameters of the disturbance signal and on the system parameters, moreover, the compensator requires only output on-line measurements.

Projection data error estimation and correction for high-resolution tomographic acoustic microscopy

In scanning tomographic acoustic microscopy (STAM), projection error correction is necessary for high-resolution tomographic reconstruction. In this paper, both phase and alignment errors are examined. These errors arise from several sources, including the quadrature receiver channels, the unknown initial phase term, and any misalignment in the rotational scan. The data acquisition process and the image formation algorithm for the STAM are reviewed, and a description of error estimation and correction is also presented. Experimental results from the STAM are included to demonstrate the capability and effectiveness of the error-removal techniques.

GPS-based tomographic reconstruction of the ionosphere

Modern space navigational system GPS Navstar and its Russian analogue GLONASS allow to measure not only phase, but also group delays of the signals propagating through the ionosphere. Possibility of total electron content absolute measurements removes problem of unknown initial phase always existing for phase measurements in 150/400 MHz band but ground-based ionosphere tomography on GPS basis is impossible for realization. To remove these dificulties we offer to replace angular transmitter movement as it is in the case of radiotomography using TRANSIT system by fast moving of a receiver located on board of low-orbital satellite, thus having saved the condition of frozen ionosphere during measurements. For this purposes it is convenient to use independent compact satellites separated from space station ALFA. It is shown that equal inclinations of GPS orbits and orbital system ALFA provide ideal conditions for 2D-radiotomography application. GPS-based tomographic reconstraction provides the possibility to study the ionosphere above the ISS orbit, which is very interesting from a scientific point of view. During some ISS orbits one can map the global structure of the ionosphere which is very useful also for monitoring and forecasting of natural hazards (earthquakes).

Generalization of the problem of optimal detection of signals in the presence of non-Gaussian passive clutter

We have synthesized asymptotically optimal detectors of weak and strong signals with random noninformative parameters against a background of non-Gaussian passive clutter. A possibility of using an adaptive approach to synthesis has been considered and an appropriate structure of an optimal detector of signals with an unknown initial phase has been found.

Estimation of an Initial Phase over Extremely Short Record-Length of a Sinewave Signal

It is known that the traditionally used statistically optimal estimator for the initial phase of a sinewave signal possesses a certain systematic bias whose value depends on an unknown initial phase. Due to the inaccuracies involved in estimating an initial phase, such an estimator fails in practice when the record length of a sinusoidal signal is less than one period. This paper presents a new algorithm for unbiased estimation of an initial phase of a sinewave burst in the presence of white noise. Such an algorithm can be thought of as a certain modification of a traditional one that is statistically optimal in the case of infinite record length of a signal under analysis. The proposed algorithm has the same structure and acts as the traditionally used one, but the systematic bias is canceled. The main difference between these two algorithms is that the orthogonal sineweighting functions in the traditional algorithm are substituted by the nonorthogonal functions whose parameters can be established a priori of the measurements. A comparative study of two algorithms is discussed. The proposed method is shown to give a more accurate estimate of an initial phase, rather than the traditional direct form. The analytic results are supplemented by a simulation study.

Unbiased estimation of an initial phase

This paper explores the problem of the unbiased estimation of the initial phase of a tone burst. Two types of initial phase estimators are investigated. The first one is based on the modification of a well-known statistically-optimal approach of estimation the phase of a continuous sinusoidal signal in the presence of a noise. The modified version permits nonlinear compensation of a priori unknown bias which is a function of a tone frequency, length of the observation interval, and of an unknown initial phase itself. The second approach employs a notch filter at the burst's ‘steady-state’ frequency. The transient of such a filter resulting from the onset of a burst can be used to deduce the signal's initial phase while the steady-state response is eliminated. Analysis shows that an estimation is unbiased and, therefore, it might be reasonably applied in high SNR environments where an estimate must be made within an extremely short length of an observation interval (less than one period).

Maximum a p o s t e r i o r i estimation of narrow-band signal parameters

Maximum a posteriori (MAP) techniques are applied to the problem of estimating the unknown parameters of a frequency modulated narrow-band signal in additive white Gaussian noise. Signals are assumed to have unknown amplitude, initial phase, and frequency versus time history, although a priori information concerning the frequency trajectory may be available. In addition, it is assumed that the signal frequency trajectory can be adequately modeled by a continuous piecewise linear function of time. It is shown that the MAP estimator maximizes a linear combination of (1) coherent match of signal induced outputs to received observations, and (2) a term dependent only upon a priori knowledge. This second term reduces to a measure of trajectory smoothness in the special case of a Gauss–Markov a priori frequency model. Lastly, a MAP detection scheme is suggested for cases in which the presence of such signals is an issue.