Abhijit Dey

Bio: Abhijit Dey is an academic researcher from Birla Institute of Technology and Science. The author has contributed to research in topics: Scintillation & Interplanetary scintillation. The author has an hindex of 1, co-authored 3 publications receiving 2 citations.

A combined iCEEMDAN and VMD method for mitigating the impact of ionospheric scintillation on GNSS signals

Abstract: Severe amplitude and phase scintillation induced by the ionospheric plasma density irregularities degrades the performance of global navigation satellite system (GNSS) receivers. Scintillation typically has adverse effects at the tracking process and thus adversely affects the raw GNSS measurements used in a number of applications. Hence, it is important to develop robust methodologies for detecting and mitigating ionospheric effects on the GNSS signals. In this paper, we propose a novel method based on the combination of improved complete ensemble empirical mode decomposition with adaptive noise (iCEEMDAN) and variational mode decomposition (VMD) methods. The proposed method employs a detrended fluctuation analysis (DFA)-based metric for robust thresholding between the scintillation-free and amplitude scintillated GNSS signals. The major contribution of the proposed method is development of novel approaches for selection of intrinsic mode functions (IMFs) based on DFA and optimised selection of [K, $${\alpha }$$ ] parameters of the VMD. The performance of the proposed method was evaluated and was observed that it is better than existing ionospheric scintillation effects mitigation algorithms for both simulated and real-time GPS scintillation datasets. The proposed method can denoise approximately 9.23–15.30 dB scintillation noise from the synthetic and 0.2–0.48 from the real scintillation index ( $$S_{4}$$ ) values. Therefore, the proposed (iCEEMDAN-VMD) method is appropriate for mitigating the ionospheric scintillation effects on the GNSS signals.

Performance Evaluation of Tracking Loop under RF Interference using NavIC Software-Receiver

Abstract: The Navigation with Indian Constellation (NavIC) S-band (i.e., 2492.028 MHz) signal is subject to interference from the unlicensed terrestrial S-band sources. The performance of both code and carrier tracking loops is degraded by external noise and interference leading to degradation in Position Velocity Timing (PVT) solutions. Because of its proximity to unlicensed S-band, the NavIC S-band is more prone to radio-frequency interference (RFI) as compared to other navigation bands. Therefore, in this paper, the effect of RFI on the parameters of the tracking loop of NavIC S-band is analyzed using a software-defined receiver (SDR), and the results are presented. It is also shown through simulations and real data that the effect of interference can be mitigated by the optimized selection of tracking loop parameters like damping ratio, noise bandwidth, and coherent integration time.

ICEEMDAN-Based Transfer Entropy between Global Commodity Classes and African Equities

Abstract: We examine the information transfer dynamics between global commodity and African equity markets to test their efficiency levels in a denoised transfer entropy approach. Our findings in the short- and medium-term scales lend support to the alternative hypothesis of market efficiency, whereas the transfer entropies at the long-term scale lend support to the efficient market hypothesis and the long-term market efficiency. Investing in a single commodity results in high uncertainty when the return pattern (history) of African equities is acknowledged. Similarly, investing in any single African equity results in high return uncertainty whilst accounting for the history of commodity markets’ returns. Short-term traders could monitor the loopholes in the market efficiency levels between global commodities and African equities to take advantage of arbitrage when needed, whilst long-term investors are assured of efficient market dynamics between global commodity markets and African equities. Regulation of markets may need to strategically incorporate news items as they fall due to either market.

Carrier-Aided Dual-Frequency Vectorized Tracking Architecture for NavIC Signals

Abstract: A new carrier-aided dual-frequency vectorized tracking (CA-DFVT) architecture for the Navigation with Indian Constellation (NavIC) is presented. CA-DFVT tracks both NavIC L5 (1176.45 MHz) and S-band (2492.028 MHz) signals concurrently. It uses the precise carrier phase measurements from the S-band signal and the unambiguous code phase measurements from the L5 signal to form a new measurement model for the extended Kalman filter (EKF) to estimate the position, velocity, and time (PVT) solutions. The new measurement model takes advantage of the benefits of the higher frequency S-band signal, i.e., less ionospheric delay and carrier phase noise, as well as the L5 signal’s inherent noise mitigation capabilities. Compared to the single-frequency approach, the dual-frequency approach in CA-DFVT eliminates the ionospheric effect and minimizes other errors, resulting in better navigation solutions. The proposed CA-DFVT enhances the reliability and robustness of NavIC signal tracking and position estimation in interference and high dynamics environments. We used static and dynamic field tests to validate the performance and robustness of the proposed CA-DFVT receiver architecture. In comparison to single-frequency (L5/S-band) vector tracking, the CA-DFVT receiver demonstrated consistent signal tracking and position estimation with higher position accuracy. In the static case, the mean horizontal position accuracy of CA-DFVT improves by approximately 2–4 and 9–14 m compared to L5-only VT and S-only VT, respectively, while, in the dynamic case, it improves by approximately 2–5 and 25–42 m, respectively.

A Novel Noise Suppression and Artifact Removal Method of Mechanomyography Based on RLS, IGWO-VMD, and CEEMDAN

Abstract: Mechanomyography (MMG) signals have extensive applications in muscle function assessment and human intention recognition. However, during signal acquisition, MMG signals are easily contaminated by noise and artifacts, which seriously affects the recognition of their characteristics. To address these issues, a novel noise suppression and artifact removal method based on recursive least square (RLS), improved Gray Wolf Optimizer-optimized variable mode decomposition (IGWO-VMD), and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is proposed. In this paper, the RLS algorithm is first applied to adaptively filter out the power line interference (PLI). Then, IGWO is designed to select the appropriate VMD parameters and use the VMD to decompose the noisy signal into band-limited intrinsic mode functions (BLIMFs). In addition, the BLIMFs are classified into the low-frequency part and high-frequency part according to the given correlation coefficient (CC) threshold value. The effective components of the low-frequency part are identified by the center frequency. Meanwhile, the high-frequency part is decomposed by CEEMDAN, and its effective components are obtained according to the proposed sample entropy threshold range. Finally, the effective components of the low and high-frequency parts are reconstructed to obtain the denoised signal to realize the extraction of useful signals. Simulation experiment results demonstrate that the proposed method outperforms the classical methods and the designed IGWO-VMD method in terms of denoising performance. The effectiveness of the proposed method is verified through the measured MMG signal experiments. The proposed method not only effectively suppresses noise and artifacts but also overcomes the limitations of VMD and CCEMDAN.

Terrestrial and Satellite-Based Positioning and Navigation Systems—A Review with a Regional and Global Perspective

Abstract: Satellite-based navigation techniques have revolutionized modern-day surveying with unprecedented accuracies along with the traditional and terrestrial-based navigation techniques. However, the satellite-based techniques gain popularity due to their ease and availability. The position and attitude sensors mounted on satellites, aerial, and ground-based platforms as well as different types of equipment play a vital role in remote sensing providing navigation and data. The presented review in this paper describes the terrestrial (LORAN-C, Omega, Alpha, Chayka) and satellite-based systems with their major features and peculiar applications. The regional and global navigation satellite systems (GNSS) can provide the position of a static object or a moving object i.e., in Kinematic mode. The GNSS systems include the NAVigation Satellite Timing And Ranging Global Positioning System (NAVSTAR GPS), of the United States of America (USA); the Globalnaya navigatsionnaya sputnikovaya sistema (GLObal NAvigation Satellite System, GLONASS), of Russia; BEIDOU, of China; and GALILEO, of the European Union (EU). Among the initial satellite-based regional navigation systems included are the TRANSIT of the US and TSYKLON of what was then the USSR which became operational in the 1960s. Regional systems developed in the last decade include the Quasi-Zenith Satellite System (QZSS) and the Indian Regional Navigation Satellite System (IRNSS). Currently, these global and regional satellite-based systems provide their services with accuracies of the order of 10–20 m using the trilateration method of surveying for civil use. The terrestrial and satellite-based augmented systems (SBAS) were further developed along with different surveying techniques to improve the accuracies up to centimeters or millimeter levels for precise applications.