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The parameter estimation problem of partly observed nonlinear discrete-time stochastic system is considered. The unobserved component of the system is a q-dimensional stable autoregressive process of the p-th order with random parameters, observed in the presence of multiplicative and additive noises. The distributions of all the noises of the system are supposed to be unknown. In the case of Gaussian...
The parameter estimation problem of a partly observed linear stochastic system is considered. The unobserved component of the system is a scalar stable autoregressive process of the p-th order, observed in presence of multiplicative and additive noises. The distributions of all the noises of the system are supposed to be unknown. The problem is to estimate the dynamic parameters of the object and...
In this paper, a blind OFDM system parameters estimation method for software defined radio (SDR) is proposed. This method sequentially estimate the sampling frequency, the number of subcarriers, the CP length as well as the timing and frequency offset in OFDM systems. The blind estimation is based on a combination of the cyclostationarity test and correlation. Monte Carlo simulation is employed to...
Many works has been made in the context of the recursive or sequential MUSIC algorithm for bearing estimation. Indeed, in some difficult scenarios as for closely spaced bearings, correlated sources and at low SNRs, the accuracy of the MUSIC algorithm can be improved by sequentially cancel the previous estimated bearings. In this paper, we propose a new algorithm, called zero-forcing based sequential...
By establishing a relationship between the classical ambiguity function and the sample cyclic cross correlation, it is shown that the former provides consistent estimates of delay and Doppler when the target echoes are observed in stationary noise. A novel fourth-order ambiguity function is proposed for estimating the delay and Doppler from random modulated Doppler-spread echoes. It is also shown...
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