On estimating parameters of a multi-component Chirp Model with equal chirp rates

Multi-component chirp signal models with equal chirp rates appear in various radar applications, e.g., synthetic aperture radar, echo signal of a rapid mobile target, etc. Many sub-optimal estimators have been developed for such models, however, these suffer from the problem of either identifiability or error propagation effect. In this paper, we have developed theoretical properties of the least squares estimators (LSEs) of the parameters of multi-component chirp model with equal chirp rates, where the model is contaminated with linear stationary errors. We also propose two computationally efficient estimators as alternative to LSEs, namely sequential combined estimators and sequential plugin estimators. Strong consistency and asymptotic normality of these estimators have been derived. Interestingly, it is observed that sequential combined estimator of the chirp rate parameter is asymptotically efficient. Extensive numerical simulations have been performed, which validate satisfactory computational and theoretical performance of all three estimators. {We have also analysed a simulated radar data with the help of our proposed estimators of multi-component chirp model with equal chirp rates, which performs efficiently in recovery of inverse synthetic aperture radar (ISAR) image of a target from a noisy data

A Computationally Efficient algorithm to estimate the Parameters of a Two-Dimensional Chirp Model with the product term

Chirp signal models and their generalizations have been used to model many natural and man-made phenomena in signal processing and time series literature. In recent times, several methods have been proposed for parameter estimation of these models. These methods however are either statistically sub-optimal or computationally burdensome, specially for two dimensional (2D) chirp models. In this paper, we consider the problem of parameter estimation of 2D chirp models and propose a computationally efficient estimator and establish asymptotic theoretical properties of the proposed estimators. And the proposed estimators are observed to have the same rates of convergence as the least squares estimators (LSEs). Furthermore, the proposed estimators of chirp rate parameters are shown to be asymptotically optimal. Extensive and detailed numerical simulations are conducted, which support theoretical results of the proposed estimators

Computationally Efficient Algorithm for Frequency Estimation of a Two-Dimensional Sinusoidal Model

In this paper, we propose a computationally faster yet conceptually simple methodology to estimate the parameters of a two-dimensional (2-D) sinusoidal model in the presence of additive white noise. We develop the large sample properties like consistency and asymptotic normality of these low-complexity estimators, and they are observed to be theoretically as efficient as the ordinary least squares estimators. To assess the numerical performance, we conduct extensive simulation studies. The results indicate that the proposed estimators can successfully replace the least squares estimators for sample size as small as 20 × 20 and for signal-to-noise ratio (SNR) as small as 12 dB

Incidence, predictors and clinical impact of permanent pacemaker insertion in women following transcatheter aortic valve implantation: Insights from a prospective multinational registry

To describe the incidence, predictors, and clinical impact of permanent pacemaker insertion (PPI) following transcatheter aortic valve replacement (TAVR) in women. Background: Data on pacemaker insertion complicating TAVR in women are scarce. Methods: The Women''s International Transcatheter Aortic Valve implantation (WIN-TAVI) is a prospective registry evaluating the safety and efficacy of TAVR in women. We included patients without preprocedural pacemakers and divided them into two groups: (1) PPI and (2) no-PPI. We identified PPI predictors using logistic regression and studied its clinical impact on the Valve Academic Research Consortium (VARC)-2 efficacy and safety endpoints. Results: Out of 1019 patients, 922 were included in the analysis. Post-TAVR PPI occurred in 132 (14.3%) patients. Clinical and procedural characteristics were similar in both groups. Pre-existing right bundle branch block (RBBB) was associated with a high risk of post-TAVR PPI (OR 3.62, 95% CI 1.85–7.06, p < 0.001), while implantation of balloon-expandable prosthesis was associated with a lower risk (OR 0.47, 95% CI 0.30–0.74, p < 0.001). Post-TAVR PPI prolonged in-hospital stay by a median of 2 days (11 [9–16] days in PPI vs. 9 [7–14] days in no-PPI, p = 0.005), yet risks of VARC-2 efficacy and safety endpoints at 1 year were similar in both groups (adjHR 0.95, 95% CI 0.60–1.52, p = 0.84 and adjHR 1.22, 95% CI 0.83–1.79, p = 0.31, respectively). Conclusion: Pacemaker implantation following TAVR is frequent among women and is associated with pre-existing RBBB and valve type. PPI prolongs hospital stay, albeit without any significant impact on 1-year outcomes