Pulsars have been an object of research in several fields notably gravitational waves, the cosmos itself, deep-space navigation, plane localization methods, among others. Pulsar signals have periods ranging from miliseconds to seconds with extremely large period accuracy, comparable to that of atomic clocks. The pulsar signal itself also has a very large bandwidth These characteristics make conventional circuit simulation techniques unusable. This paper considers the characteristics of the pulsar signals and implements a prototype that generates a signal resembling the signals emitted by pulsars i.e., a pulsar generator. Such a simulator is very useful to assess pulsar receiver real time performance because pulsar signals are very difficult to capture on Earth due to its very low power, large bandwidth an also because of atmospheric effects which degrade the signal. The prototype allows to simulate different pulsar signals, in real time and is portable. Furthermore, the signal to noise ratio (SNR) can be adjusted from -14.9 to 19.7 dB and the signal bandwidth can me modified by using a set of different filters.

Pulsars emit broadband electromagnetic radiation, with an individual signature (period and shape), ranging from radio to X-ray and gamma-ray frequencies. For the purpose of navigation the pulsars of interest are fast rotating neutron stars that emit short stable periodic pulses, having periods between milliseconds and seconds. By detecting a set of known pulsars, it is possible to use them as beacons for navigation in celestial coordinates, being seen as the only truly navigation solution for deep-space navigation [1]. In this demo a proof of concept is presented for an innovative receiver architecture, overcoming, some of the issues presented in the paper entitled “Radio Pulsar Receiver Systems for Space Navigation” [2]. Furthermore, a fake pulsar generation board was developed and also an acquisition board, for both, simulate a pulsar signal and to process the data from the receiver and acquire the pulsar signal from noise.

An alternative ARMA model parameterization method for approximating the Clarke's correlation statistics is proposed. Instead of using the standard autocorrelation function in the estimation process it considers the reflection coefficients sequence, an alternative second order statistic. It is shown that the higher the order of the ARMA(p, p-1) model, the more ill-conditioned the problem becomes. The proposed method includes an automatic ill-conditioning regularization method which does not require a priori knowledge of the regularization parameter as is the case with other methods. Two ARMA(p, q) models of different orders are obtained and discussed, in particular an ARMA(12,11) model and an ARMA(14,13) model. Both models provide very good approximations to the Clarke's autocorrelation function and they are compared with other proposed ARMA(p, q) models from the literature.

In this paper the problem of generating a stationary band-limited Gaussian random vector with arbitrary complex autocorrelation by the inverse discrete Fourier transform (IDTF) algorithm is considered. Instead of using the classical frequency mask (FM), determined from samples of the (band-limited) target power spectral density (PSD) of the process, a new FM is obtained by matching the autocorrelation obtained with the IDFT algorithm to a desired arbitrary autocorrelation. Example results presented show that the new FM is able to significantly increase the autocorrelation accuracy of the generated process at no additional online computational cost.

An ARMA(p,q) model parameterization method is outlined and proposed for approximating the Clarke's theoretical autocorrelation function. The method uses a strategy that consists of computing the AR coefficients in a preliminary stage and then, in a subsequent stage, computing the MA coefficients. In the first stage it considers a "redesigned" least squares modified Yule Walker equations estimator for determining the AR coefficients, and in the second stage it uses the Durbin's method for computing the MA coefficients. An ARMA(7,6) model and an ARMA(14,13) model are obtained for approximating the Clarke's theoretical correlation statistics considering a nominal discrete-time maximum Doppler frequency of fD=0.05. The accuracy of the fitting provided with the two obtained ARMA(p,q) models is compared with results from the literature. Both the ARMA(7,6) and the ARMA(14,13) models provide very good fitting.

In this paper we propose an efficient and accurate method for imposing a desired spatial correlation between Multiple-Input Multiple-Output (MIMO) channels. Given an input matrix constructed so that each column contains a sampled version of each MIMO subchannel, the proposed method imposes the desired spatial correlation by rearranging the samples in each column. This technique is based on the Iman-Conover(IC) method which is distribution-free. This method is computationally unexpensive and the simulation results show a very good agreement between the desired and the simulated spatial correlation.

In this letter we present new and simple closed form expressions for the true Cramer-Rao lower bound (CRB) for data-aided (DA) joint and individual carrier frequency offset and symbol timing estimation from a linearly modulated waveform transmitted over an AWGN channel. The bounds are derived under a carrier-phase-independent (CPI) estimation strategy wherein the carrier phase is viewed as a nuisance parameter and assumed to have a worst-case noninformative uniform distribution over [-¿, ¿]. The computation of these CRBs requires only a single numerical integration. In addition, computationally simpler yet highly accurate asymptotic lower bounds are presented. As particularizations, new bounds for individual CPI frequency estimation with known symbol timing from M-PSK and continuous wave (CW) signals are also reported.

This paper presents a Rayleigh fading mobile-to- mobile channel simulator based on a modified Karhunen-Loeve orthogonal expansion of a complex Gaussian fading process. The method is similar to the well-known IFFT method but with a different frequency mask. The simulation accuracy is assessed by the computation of power margins (for the autocorrelation) and of Kullback-Leibler divergence (for the envelope probability density function) of the simulated fading process. The results demonstrate a good agreement with the theory and a slight improvement relative to the IFFT method.

While the LMS algorithm and its normalized version (NLMS), have been thoroughly used and studied, and connections between the Kalman filter and the RLS algorithm have bean established, the connection between the Kalman filter and the LMS algorithm has not received much attention. By linking these two algorithms, a new normalized LMS algorithm can be derived that has some advantages to the classical one. Firstly, its stability is guaranteed since it is a special case of the Kalman filter. Secondly, it suggests a new way to control the step size that results in optimum convergence for a large range of input signal powers, that occur in many applications. Finally, it prevents measurement noise amplification that occurs in the NLMS algorithm for low order filters, like the ones used in OFDM equalization systems.

In this letter, we propose a systematic technique for optimum data-sequence design for data-aided (DA) estimation of synchronization parameters. It is assumed that the system operates in burst mode, transmitting a linearly modulated information signal over an additive white Gaussian noise channel. The method is based on the minimization of the corresponding Crameacuter-Rao lower bound subject to a power constraint and is applied in four practical receiver synchronization contexts: estimation of the symbol timing with known carrier frequency offset and either known or unknown carrier phase, joint estimation of the symbol timing and carrier phase with known carrier frequency offset, and joint estimation of the carrier phase and carrier frequency offset with known symbol timing

In this letter, we derive new results for the statistics of the complex random variablez=DeltaSigman=1Nxn2=z1+jzQ=rejphiwhere {xn} is a set of mutually independent complex-valued Gaussian random variables with arbitrary means and equal variances. Each random variablexnis assumed to have independent real and imaginary components with equal variance for alln. Expressions are derived for the joint probability density function (pdf) of (z1,zQ), for the joint pdf of (r,phi) and also for the marginal pdf of the modulusr. An useful Fourier series expansion for the pdf of the phase phi is also derived. As an application of the results, a theoretical performance analysis of the well-known nondata-aided Viterbi and Viterbi feedforward carrier phase estimator operating with BPSK signals is presented. In particular, the expressions for the exact pdf, variance, and equivocation probability of the carrier phase estimates are derived.

In this paper, we present the derivation and analysis of the true Crame/spl acute/r-Rao lower bound (CRB) for the variance of unbiased, data-aided (DA) symbol-timing estimates, obtained from a block of K samples of a linearly modulated information signal, transmitted through an additive white Gaussian noise channel with random carrier phase. We consider a carrier-phase-independent time-delay estimation scenario wherein the carrier phase is viewed as an unwanted or nuisance parameter. The new bounds require only a moderate computational effort and are tighter than the CRB for the variance of unbiased time-delay estimates obtained under the assumption that the carrier phase is known. These bounds are particularly useful to assess the ultimate accuracy that can be achieved by pilot-assisted symbol synchronizers. Conversely, they may be used to evaluate data sequence suitability for the purpose of time-delay estimation. Comparison of the actual variance of a DA feedforward timing estimator with the new bounds show that these are attainable by practical synchronizers.

In this letter, we derive a new Miller-Chang lower bound (MCB) for the variance of unbiased non-data-aided (NDA) carrier phase estimates obtained from a block of N samples of a linearly modulated pulse-amplitude modulation or quadrature-amplitude modulation information signal, transmitted through an additive white Gaussian noise channel. This bound is tighter than the corresponding Crame/spl acute/r-Rao lower bound (CRB) for data-aided or continuous-wave carrier phase estimation (CW-CRB), particularly when N is small. For some given N and sufficiently high signal-to-noise ratios, the MCB is tighter than the corresponding true NDA CRB. The main limitation of this new MCB is that its application is restricted to carrier phase estimators which are unbiased for all possible values of the received symbol sequence.

We derive new Cramer-Rao lower bounds (CRBs) for the estimation of carrier phase and frequency offset from an unmodulated carrier or from a M-PSK data signal. The new CRBs are obtained formally from the exact likelihood function for the carrier phase and frequency offset, build from a block of received phase samples, and are applicable for a general alphabet size M. The bounds are compared with other previously obtained bounds (which also take into account the effect of random phase modulation) and with the performance of some popular feedforward algorithms for carrier phase and frequency offset estimation.

A data-aided (DA) feedforward symbol synchronizer based upon the maximum-likelihood (ML) criterion is proposed. The algorithm is carrier-phase independent and is designed for operation in burst-mode, narrow-band communication systems employing linear modulation. The accuracy of the proposed algorithm is assessed by simulation using QPSK signaling. The results show that the performance of the proposed synchronizer is very close to the theoretical minimum limit (variance of the estimates near the Cramer-Rao lower bound) and is also significantly better than that of other popular circuits such as the square-law synchronizer.