Search Results (25)

In vehicle GNSS/INS integrated navigation, robust and adaptive algorithms have become one of the key technologies for achieving a comprehensive PNT due to their ability to control the gross errors of the observation model and dynamic model. The Sage–Husa algorithm is widely used in optimizing the Kalman filter due to its ability to estimate the observation or state covariance without prior information. However, the quality of observations in complex environments is prone to large fluctuations, so the averaging method is not suitable for dynamic navigation. To solve this problem, this article designs a double window structure and introduces a time-dependent fading weighted factor. At the same time, a logarithmic form factor constructor is proposed in order to avoid anomalies in the robust and adaptive factor. The traditional innovation adaptive filter is improved and turned into a multi-factor adaptive filter. In this paper, an improved fault detection algorithm is used to combine a robust algorithm with an adaptive algorithm to adapt to different gross errors in different scenarios. The experimental results of complex scenarios show that the position RMSE of the improved algorithm in the east, north, and height directions is 0.68 m, 0.71 m, and 1.05 m, respectively, which are reduced by 39.3%, 39.3%, and 70.3% compared to the EKF. Full article

This paper presents research on the security performance of a multi-user interference-based mixed RF/FSO system based on SWIPT untrusted relay. In this work, the RF and FSO channels experience Nakagami-m fading distribution and Málaga (M) turbulence, respectively. Multiple users transmit messages to the destination with the help of multiple cooperating relays, one of which may become an untrusted relay as an insider attacker. In a multi-user network, SWIPT acts as a charging device for each user node. In order to prevent the untrusted relays from eavesdropping on the information, some users are randomly assigned to transmit artificial noise in order to interfere with untrusted relays, and the remaining users send information to relay nodes. Based on the above system model, the closed-form expressions of secrecy outage probability (SOP) and average secrecy capacity (ASC) for the mixed RF/FSO system are derived. The correctness of these expressions is verified by the Monte Carlo method. The influences of various key factors on the safety performance of the system are analyzed by simulations. The results show that the security performance of the system is considerably improved by increasing the signal–interference noise ratio, the number of interfering users, the time distribution factor and the energy conversion efficiency when the instantaneous signal-to-noise ratio (SNR) of the RF link instantaneous SNR is low. Full article

Various factors such as natural disasters, vandalism, weather, and environmental conditions can affect the physical state of traffic signs. The proposed model aims to improve detection of traffic signs affected by partial occlusion as a result of overgrown vegetation, displaced signs (those knocked down, bent), perforated signs (those damaged with holes), faded signs (color degradation), rusted signs (corroded surface), and de-faced signs (placing graffiti, etc., by vandals). This research aims to improve the detection of bad traffic signs using three approaches. In the first approach, Spiral Pooling Pyramid-Fast (SPPF) and C3TR modules are introduced to the architecture of Yolov5 models. SPPF helps provide a multi-scale representation of the input feature map by pooling at different scales, which is useful in improving the quality of feature maps and detecting bad traffic signs of various sizes and perspectives. The C3TR module uses convolutional layers to enhance local feature extraction and transformers to boost understanding of the global context. Secondly, we use predictions of Yolov5 as base models to implement a mean ensemble to improve performance. Thirdly, test time augmentation (TTA) is applied at test time by using scaling and flipping to improve accuracy. Some signs are generated using stable diffusion techniques to augment certain classes. We test the proposed models on the CCTSDB2021, TT100K, GTSDB, and GTSRD datasets to ensure generalization and use k-fold cross-validation to further evaluate the performance of the models. The proposed models outperform other state-of-the-art models in comparison. Full article

This paper introduces a novel filter algorithm termed as an MKMC-CSVSF which combined square-root cubature Kalman (SR-CKF) and smooth variable structure filtering (SVSF) under multi-kernel maximum correntropy criterion (MKMC) for accurately estimating the state of the fully submerged hydrofoil craft (FSHC) under the influence of uncertainties and multivariate heavy-tailed non-Gaussian noises. By leveraging the precision of the SR-CKF and the robustness of the SVSF against system uncertainties, the MKMC-CSVSF integrates these two methods by introducing a time-varying smooth boundary layer along with multiple fading factors. Furthermore, the MKMC is introduced for the adjustment of kernel bandwidths across different channels to align with the specific noise characteristics of each channel. A fuzzy rule is devised to identify the appropriate kernel bandwidths to ensure filter accuracy without undue complexity. The precision and robustness of state estimation in the face of heavy-tailed non-Gaussian noises are improved by modifying the SR-CKF and the SVSF using a fixed-point approach based on the MKMC. The experimental results validate the efficacy of this algorithm. Full article

This paper presents research on the physical layer security performance of a multi-user mixed RF/FSO system based on optimal user interference. In this system model, the RF link experiences Rayleigh fading, and the FSO link follows the Fischer–Snedecor $\mathcal{F}$ distribution. The system adopts a double-hop-decode-and-forward (DF) relay scheme. We also consider the effect of directivity errors in the FSO link and assume the presence of an illegal eavesdropper with a single antenna near the RF link. The source node controls the energy collection and information forwarding using a multi-user structure based on simultaneous wireless information and power transfer (SWIPT). We select the optimal user to jam the eavesdropper’s communication. We derive closed-form expressions for the mixed RF/FSO communication system’s secrecy outage probability (SOP) and average secrecy capacity (ASC). Monte Carlo simulations are performed to verify the accuracy of these expressions. By formulating and simulating the simulation system, the impact of various important factors on the mixed system’s physical layer security (PLS) is analyzed. The analysis indicates that increasing the number of antennas and interference signal-to-noise ratio (SNR) of the optimal user, the time allocation factor and energy conversion efficiency, and the improvement in the quality of atmospheric channels with improved weather will significantly enhance this system’s PLS. Full article

Internet of Things (IoT) systems cooperative with unmanned aerial vehicles (UAVs) have been put into use for more than ten years, from transportation to military surveillance, and they have been shown to be worthy of inclusion in the next wireless protocols. Therefore, this paper studies user clustering and the fixed power allocation approach by placing multi-antenna UAV-mounted relays for extended coverage areas and achieving improved performance for IoT devices. In particular, the system enables UAV-mounted relays with multiple antennas together with non-orthogonal multiple access (NOMA) to provide a potential way to enhance transmission reliability. We presented two cases of multi-antenna UAVs such as maximum ratio transmission and the best selection to highlight the benefits of the antenna-selections approach with low-cost design. In addition, the base station managed its IoT devices in practical scenarios with and without direct links. For two cases, we derive closed-form expressions of outage probability (OP) and closed-form approximation ergodic capacity (EC) generated for both devices in the main scenario. The outage and ergodic capacity performances in some scenarios are compared to confirm the benefits of the considered system. The number of antennas was found to have a crucial impact on the performances. The simulation results show that the OP for both users strongly decreases when the signal-to-noise ratio (SNR), number of antennas, and fading severity factor of Nakagami-m fading increase. The proposed scheme outperforms the orthogonal multiple access (OMA) scheme in outage performance for two users. The analytical results match Monte Carlo simulations to confirm the exactness of the derived expressions. Full article

Many studies have focused on the smartphone-based global navigation satellite system (GNSS) for its portability. However, complex urban environments, such as urban canyons and tunnels, can easily interfere with GNSS signal qualities. Current smartphone-based positioning technologies using the GNSS signal still pose great challenges. Since the last satellite of the BeiDou navigation system (BDS) was successfully launched on 23 June 2020, it is possible to use a low-cost Android device to realize the localization based on the BDS signals worldwide. This research focuses on smartphone-based outdoor pedestrian navigation utilizing the GPS/BDS multi-constellation system. To improve the localization accuracy, we proposed the Weighted Factor Graph Optimization localization model (W-FGO). In this paper, firstly, we evaluate the signal qualities of the BDS via the data collected by the static experiment. Then, we structure the cost function based on the pseudo-range and the time series data for the traditional Factor Graph Optimization (FGO). Finally, we design the weight model based on the signal quality of each satellite and the time fading factor to further improve the localization accuracy of the conventional FGO method. An Android smartphone is utilized to collect the GNSS data for the evaluation and the localization. The experiment results demonstrate the superior performance of the proposed method. Full article

A new multi−carrier orthogonal double bit rate differential chaotic shift keying (MC−ODBR−DCSK) communication system is presented in this paper. With two composite signals generated by an orthogonal chaotic signal generator as reference signals, 2M bits of information data are transmitted on M−channel subcarriers, improving transmission speed and energy efficiency. In addition, the receiver does not require a radio frequency (RF) delay circuit to demodulate the received data, which makes the system easier to implement. This paper analyzes Data−energy−to−Bit−energy Ratio (DBR) of the system. The bit error rate performance of the system is simulated to verify the impact of parameters such as chaotic maps, semi-spread spectrum factor, and sub-carrier number. At the same time, the bit error rate performance of the MC−ODBR−DCSK system is compared with traditional DCSK systems in Rician fading and additive Gaussian white noise (AWGN) channels. Full article

This paper improves energy efficiency and communications reliability for wireless transmission under $\kappa$-$\mu$ shadowed fading (i.e., integrating all channel impairments including path loss, shadowing, fading) and hardware impairment by employing a nonlinear energy harvester and multi-antenna power transmitter. To this end, this paper provides explicit formulas for outage probability. Numerous results corroborate these formulas and expose that energy-harvesting nonlinearity, hardware impairment, and channel conditions drastically deteriorate system performance. Notwithstanding, energy-harvesting nonlinearity influences system performance more severely than hardware impairment. In addition, desired system performance is accomplished flexibly and possibly by choosing a cluster of specifications. Remarkably, the proposed communications scheme obtains the optimal performance with the appropriate selection of the time-splitting factor. Full article

Hypersonic targets have complex motion states and high maneuverability. The traditional interactive multi-model (IMM) has low tracking accuracy and a slow convergence speed. Therefore, this paper proposes a strong tracking cubature Kalman filter (CKF) adaptive interactive multi-model (AIMM) based on multiple fading factors. Firstly, this paper analyzes the structure of the CKF algorithm, introduces the fading factor of the strong tracking algorithm into the covariance matrix of the time update and measurement update, and adjusts the filter gain online and in real time, which can reduce the decline infilter accuracy caused by model mismatch. Secondly, Singer model, “current” statistical (CS) model, and Jerk model are selected in the model set of IMM and introduced singular value decomposition (SVD) decomposition to solve the problem that Cholesky decomposition cannot be performed in the CKF due to the model dimension expansion. Last, an adaptive algorithm for the Markov matrix in the IMM is proposed. The transition probability was adaptively modified by the value of the model likelihood function to enhance the proportion of matching models. The simulation results show that the proposed algorithm enhanced the proportion of matching models in the IMM and improved the tracking accuracy by 16.51% and the convergence speed by 37.5%. Full article

To realize the in-motion alignment of the strapdown inertial navigation system (SINS) under the geographic latitude uncertainty, we propose a latitude estimation and in-motion alignment method based on the integral dynamic window and polynomial fitting (IDW-PF) and improved Kalman filter (IKF). First, the integral dynamic window (IDW) is designed to smooth out the high-frequency line motion interference and accelerometer noise. Second, the specific force integral is performed for a cubic polynomial fitting (PF) with time as an independent variable to further suppress the line motion interference. Simultaneously, the latitude is estimated according to the geometric relationship between the angle of the gravitational acceleration vectors at different moments and the latitude. Finally, the IKF based on the multi-fading factor is designed for the in-motion alignment of SINS. A simulation experiment is conducted to verify the proposed latitude estimation and in-motion alignment method. The results indicate that the latitude can be estimated well by the method based on the IDW-PF; the mean and standard deviation of the estimated latitude can achieve −0.016° and 0.013° within 300 s. The trapezoidal maneuvering path is optimal when IKF is used, the pitch error is 0.0002°, the roll error is 0.0009° and the heading error is −0.0047° after the alignment ends at 900 s. Full article

The traditional cable-based geophone network is an inefficient way of seismic data transmission owing to the related cost and weight. The future of oil and gas exploration technology demands large-scale seismic acquisition, versatility, flexibility, scalability, and automation. On the one hand, a typical seismic survey can pile up a massive amount of raw seismic data per day. On the other hand, the need for wireless seismic data transmission remains immense. Moving from pre-wired to wireless geophones faces major challenges given the enormous amount of data that needs to be transmitted from geophones to the on-site data collection center. The most important factor that has been ignored in the previous studies for the realization of wireless seismic data transmission is wireless channel effects. While transmitting the seismic data wirelessly, impairments like interference, multi-path fading, and channel noise need to be considered. Therefore, in this work, a novel amalgamation of blind channel identification and deep neural networks is proposed. As a geophone already is responsible for transmitting a tremendous amount of data under tight timing constraints, the proposed setup eschews sending any additional training signals for the purpose of mitigating the channel effects. Note that the deep neural network is trained only on synthetic seismic data without the need to use real data in the training process. Experiments show that the proposed method gives promising results when applied to the real/field data set. Full article

Large-scale fading models play an important role in estimating radio coverage, optimizing base station deployments and characterizing the radio environment to quantify the performance of wireless networks. In recent times, multi-frequency path loss models are attracting much interest due to their expected support for both sub-6 GHz and higher frequency bands in future wireless networks. Traditionally, linear multi-frequency path loss models like the ABG model have been considered, however such models lack accuracy. The path loss model based on a deep learning approach is an alternative method to traditional linear path loss models to overcome the time-consuming path loss parameters predictions based on the large dataset at new frequencies and new scenarios. In this paper, we proposed a feed-forward deep neural network (DNN) model to predict path loss of 13 different frequencies from 0.8 GHz to 70 GHz simultaneously in an urban and suburban environment in a non-line-of-sight (NLOS) scenario. We investigated a broad range of possible values for hyperparameters to search for the best set of ones to obtain the optimal architecture of the proposed DNN model. The results show that the proposed DNN-based path loss model improved mean square error (MSE) by about 6 dB and achieved higher prediction accuracy R2 compared to the multi-frequency ABG path loss model. The paper applies the XGBoost algorithm to evaluate the importance of the features for the proposed model and the related impact on the path loss prediction. In addition, the effect of hyperparameters, including activation function, number of hidden neurons in each layer, optimization algorithm, regularization factor, batch size, learning rate, and momentum, on the performance of the proposed model in terms of prediction error and prediction accuracy are also investigated. Full article

This paper presents a novel multiple strong tracking adaptive square-root cubature Kalman filter (MSTASCKF) based on the frame of the Sage–Husa filter, employing the multi-fading factor which could automatically adjust the Q value according to the rapidly changing noise in the flight process. This filter can estimate the system noise in real-time during the filtering process and adjust the system noise variance matrix Q so that the filtering accuracy is not significantly reduced with the noise. At the same time, the residual error in the filtering process is used as a measure of the filtering effect, and a multiple fading factor is introduced to adjust the posterior error variance matrix in the filtering process, so that the residual error is always orthogonal and the stability of the filtering is maintained. Finally, a vibration test is designed which simulates the random noise of the short-range guided weapon in flight through the shaking table and adds the noise to the present simulation trajectory for semi-physical simulation. The simulation results show that the proposed filter can significantly reduce the attitude estimation error caused by random vibration. Full article

We characterize the LoRa channel in terms of multi-path fading, loss burstiness, and assess the benefits of Forward Error Correction as well as the influence of frame length. We make these observations by synthesizing extensive experimental measurements realized with The Things Network in a medium size city. We then propose to optimize the LoRaWAN Adaptive Data Rate algorithm based on this refined LoRa channel characterization and taking into account the LoRaWAN inherent macro-diversity from multi-gateway reception. Firstly, we propose ${\mathit{ADR}}_{\mathrm{opt}}$, which adjusts Spreading Factor and frame repetition number to maintain the communication below a target Packet Error Rate ceiling with optimized Time-On-Air. Secondly, we propose ${\mathit{ADR}}_{\mathrm{IFECC}}$, an extension of ${\mathit{ADR}}_{\mathrm{opt}}$ in case an Inter-Frame Erasure Correction Code is available. The resulting protocol provides very high reliability even over low quality channels, with comparable Time on Air and similar downlink usage as the currently deployed mechanism. Simulations corroborate the analysis, both over a synthetic random wireless link and over replayed real-world packet transmission traces. Full article