No abstract

No abstract

Summary Continuous wave interference has found to be one of the major menaces that deter the performance of the Indian Regional Navigation Satellite System (IRNSS) receivers for seamless positioning and navigation. In this paper, a novel hybrid jamming mitigation method based on variational mode decomposition (VMD) and wavelet packet transform (WPT) has been proposed. VMD is used to decompose the received signal into various components referred to as intrinsic mode functions (IMFs). To have an optimum decomposition of the signal, the mode decomposition number of VMD is determined by employing the kurtosis principle. Then, a threshold based on the mutual information index is constructed to differentiate the information dominant and interference dominant modes. The information dominant modes are then processed by the wavelet packet filter to eliminate the remaining effects of jamming and noise present. Finally, the filtered modes and the retained modes are used to reconstruct the desired signal. The performance of the technique is analyzed in the presence of single‐tone, multitone, and chirp jamming scenarios with different levels of jamming power. The proposed method has been tested by simulations in comparison with the standard algorithms. Results show that the proposed hybrid algorithm outperforms the standard algorithms in reducing the jamming signal effectively.

No abstract

No abstract

Reliable positioning, timing, and navigation services have become vitally important in safety and security applications. Hence, the need for Global Navigation Satellite Systems (GNSS) is growing continually. However, Continuous Wave Interference (CWI) was found to be one of the major potential threats of GNSS systems which degrades the receiver's performance. So, in this paper, a new approach using Improved Variational Mode Decomposition and Wavelet Packet Decomposition (IVMD‐WPD) has been proposed to mitigate CWI in NAVigation with Indian Constellation (NavIC) receivers. Although VMD is considered as an excellent signal analysis tool in decomposing non‐stationary and complex signals, the accuracy of the decomposition results depends upon the parameter setting. To address this, firstly, Normalized Kurtosis Energy Ratio (nKER) evaluation index is constructed. Then, the principle of nKER maximum is implemented to find the optimal parameters of VMD. Using the optimized parameters, the received signal is decomposed by IVMD into sub‐signals. Secondly, the mutual information index is introduced to extract the information dominant modes. The extracted modes are then processed by wavelet packet filter and finally, the desired signal is reconstructed. The proposed IVMD‐WPD method not only reduces the jamming efficiently but also overcomes the limitations of VMD. Moreover, by integrating IVMD with wavelet packet filter, the remaining effects of jamming and noise present in desired modes can be filtered thereby enhancing the performance. Simulation results reveal that the proposed method performs better in comparison with the conventional techniques in case of a single tone, multi‐tone, and chirp jamming environments.

Summary Underwater wireless sensor networks (UWSNs) contain quite a lot of components such as vehicles and sensors that are deployed in a specific acoustic area to perform collaborative monitoring and data collection errands. These networks are adopted interactively between diverse nodes and ground‐based stations. Currently, UWSNs face problems and challenges that pertain to limited bandwidth, media access control, high propagation delay, 3D topology, spectrum sensing, resource utilization, routing, and power constraints. This proposal deals with the intelligent spectrum sensing in underwater cognitive sonar communication networks (CSCN). Here, the improved performance of spectrum sensing in underwater communication is attained by optimizing the cooperative spectrum sensing and data transmission. The parameters of system like subchannel allocation and transmission power is optimized by a new hybrid meta‐heuristic algorithm by integrating the concepts of deer hunting optimization algorithm (DHOA) and lion algorithm (LA) termed as lion‐enabled DHOA (L‐DHOA). The main intention of optimizing these parameters is to maximize the spectrum efficiency (SE) and energy efficiency (EE) of the underwater channel communication system. From the analysis, with respect to convergence rate, minimum detection probability, and local sensing time, it is proved that the novel hybrid optimization algorithm keeps a great role in making the trade‐off between the SE and EE in underwater channel modeling.

No abstract