Multipath Propagation Model Research Articles

SALOS-A UWB Single-Anchor Indoor Localization System Based on a Statistical Multipath Propagation Model.

Among other methods, UWB-based multi-anchor localization systems have been established for industrial indoor localization systems. However, multi-anchor systems have high costs and installation effort. By exploiting the multipath propagation of the UWB signal, the infrastructure and thus the costs of conventional systems can be reduced. Our UWB Single-Anchor Localization System (SALOS) successfully pursues this approach. The idea is to create a localization system with sophisticated signal modeling. Therefore, measured reference, like fingerprinting or training, is not required for position estimation. Although SALOS has already been implemented and tested successfully in an outdoor scenario with multipath propagation, it has not yet been evaluated in an indoor environment with challenging and hardly predictable multipath propagation. For this purpose, we have developed new algorithms for the existing hardware, mainly a three-dimensional statistical multipath propagation model for arbitrary spatial geometries. The signal propagation between the anchor and predefined candidate points for the tag position is modeled in path length and complex-valued receive amplitudes. For position estimation, these modeled signals are combined to multiple sets and compared to UWB measurements via a similarity metric. Finally, a majority decision of multiple position estimates is performed. For evaluation, we implement our localization system in a modular fashion and install the system in a building. For a fixed grid of 20 positions, the localization is evaluated in terms of position accuracy. The system results in correct position estimations for more than 73% of the measurements.

Damage imaging using multipath-scattered Lamb waves under a sparse reconstruction framework

This paper presents a damage sparse imaging method using multipath-scattered Lamb waves. It leverages a large number of echoes and reverberations in the recorded signal that may be usually ignored in conventional methods. First, reflections of Lamb waves at free edges are viewed as waves transmitted from a virtual transducer which is located at the mirror point of the actual one. On this basis, an optimized transducers-layout strategy is proposed based on the multipath propagation model of the Lamb wave. Benefiting from that, the direct damage-scattered wave and several waves scattered by both the damage and edges could be separately identified in the time domain, and further, each wave could be matched with a sensing path (either actual or virtual) in the expanded sensor network. Subsequently, a dictionary is constructed from the Lamb wave propagation and scattering model. By solving the sparse reconstruction problem, the pixel value of each point in the region of interest is obtained, and the whole area can be finally visualized. The proposed method is validated using experiments conducted on an aluminum plate with simulated damages. Results show that the damages can be correctly detected and accurately localized with only a single transmitter–receiver pair.

Path Loss and Auxiliary Communication Analysis of VANET in Tunnel Environments

Vehicular ad hoc network (VANET) communications face severe fading problems due to the signal reflections and diffractions within tunnels. Unlike the open road, the space of a tunnel is very limited, so VANET communication performance in a tunnel is seriously affected. In the process of signal transmission, the reflected signal is symmetrical with the incident signal after it is reflected by the road and the wall. In this paper, we establish a mathematical model of path loss for V2V (Vehicle-to-Vehicle) communication based on the principle of signal reflection symmetry in tunnels and considering several factors, such as the tunnel surface and the color of the tunnel wall. In addition, we use cooperative communication to form a virtual multiple-input multiple-output (V-MIMO) system, to improve the communication quality in tunnels. In the proposed system, the OBU (On-Board-unit) and RSU (Road-Side-Unit) share each other’s antennas, so that wireless cooperative communication can be employed, without increasing the number of antennas in a one-way tunnel. Therefore, this multipath fading internal electromagnetic wave propagation model can be used to improve performance. A deep reinforcement learning algorithm was used to solve the pairing problem to obtain a more accurate OBU and RSU pair, to form a V-MIMO system. Here, the RSU is regarded as an agent and interacts with the OBU in the tunnel. The optimal strategy was learned in a real-time changing simulation environment, and the experiment verified the convergence of the algorithm. The simulation results showed that, compared with the Q-learning based scheme, the optimal matching algorithm based on V-MIMO and a DQN (Deep Q-network) could effectively reduce the probability of transmission outages and improve the communication efficiency in tunnels.

Elevation angle measurement for low‐angle targets using synthesized pattern null method

AbstractThis study proposes a novel method, that is, synthesized pattern null (SPN) method. The SPN method has very low computational complexity, which can be fully applied to all range‐azimuth resolution cells of the actual radar system. It does not depend on the multipath propagation model and has good robustness. This study presents the derivation process, the simulation results, and comparative experimental results of the actual radar system. The results reveal that the SPN method can significantly reduce the elevation angle error for low‐angle targets, and the root mean square error (RMSE) can be reduced to about 1/15 beam width. Moreover, compared with the synthesized vector maximum likelihood method, this method has similar angle measurement performance, much lower computational complexity and better robustness.

A Multipath Model for Disturbance Propagation in Electrical Power Networks

This paper deals with the nature of propagation of disturbance spectrum through the power lines of an electric power system. A multi-path propagation model is proposed based on the reflection and refraction theory of wave propagation. The developed model captures the spatio-temporal aspect of disturbance propagation and is validated for a wide band of frequency. The proof of concept for the developed model is shown on a 2-bus system with a disturbance at a point between the buses. Results are validated in time domain with electromagnetic transient simulation programming.

NLOS Positioning for Building Layout and Target Based on Association and Hypothesis Method

Localization of non-line-of-sight (NLOS) targets in the complex urban environment have attracted significant attention in recent years. However, the requirement for precise prior information about the environment is idealistic. It is challenging to know the environmental information in the blind area of vision in advance of practical applications. This paper proposes a joint estimation algorithm for building layout and target position in the L-shaped scene without any prior information. Specifically, a round-trip multipath propagation model is first developed for the cases of diffraction and multiple reflections. Then, the received echo signal is preprocessed with moving target identification (MTI), back-projection (BP) imaging, and image segmentation. In addition, the target points, which are screened by geometric association, are further matched and estimated by the multipath ghost’s hypothesis method, thus realizing the joint perceptual estimation of the building layout and the target position. Finally, electromagnetic (EM) simulations and experimental measurements are used to validate the effectiveness of the proposed algorithm.

Target Height Measurement under Complex Multipath Interferences without Exact Knowledge on the Propagation Environment

This paper investigates the direction-of-arrival (DOA) estimation-based target localization problem using an array radar under complex multipath propagation scenarios. Prevalent methods may suffer from performance degradation due to the deterministic signal model mismatch, especially when the exact knowledge of a propagation environment is unavailable. To cope with this problem, we first establish an improved signal model of multipath propagation for low-angle target localization scenarios, where the dynamic nature of convoluted interferences induced by complex terrain reflections is taken into account. Subsequently, an iterative implementation-based target localization algorithm with the improved propagation model is proposed to eliminate the detrimental effect of coherent interferences on target localization performance. Compared to existing works, the proposed algorithm can maintain satisfactory estimation performance in terms of target location parameters, even in severe multipath interference conditions, where the decorrelation preprocessing and accurate knowledge about the multipath propagation environment are not required. Both simulation and experimental results demonstrate the effectiveness of the proposed propagation model and localization algorithm.

Multipath Imaging for NLOS Targets Behind an L-Shaped Corner With Single-Channel UWB Radar

Non-line-of-sight (NLOS) detection is widely encountered in military and civilian fields, such as urban battles and disaster rescues. In this study, a novel multipath imaging approach is proposed to solve the problem of multi-target localization behind an L-shaped corner for a single-channel ultra-wide-band (UWB) radar. Specifically, a multipath propagation model based on an L-shaped corner is established, and the positions of virtual radars are analyzed by the specular reflection feature of electromagnetic wave, which forms a virtual array aperture to achieve enough image resolution. Then, the radar echo is mapped based on each propagation path to form multiple images. Finally, according to the trajectory distribution in each image, the incoherent addition is exploited to fuse the multiple images to focus on the target locations. Simulation and experimental results demonstrate that the estimated target positions are consistent with the actual target locations, and the proposed multipath imaging algorithm is applicable in the case of partial path loss.

Joint Estimation of NLOS Building Layout and Targets via Sparsity-Driven Approach

Non-line-of-sight (NLOS) detection is an enduring topic as it provides a powerful tool to monitor visually blocked areas. Currently, the NLOS detection requires precise prior knowledge of building layout, which limits its further applications in practice. In this paper, we consider the problem of joint estimation of building layout and target location in the NLOS scenario by exploiting multipath returns. Specifically, first, the building layout is simplified into combined linear equations with unknown parameters. In this way, we establish a parametrized multipath propagation model in the multiple targets NLOS scenario for the multiple-input-multiple-output (MIMO) radar, which is used in the image reconstruction and layout estimation problem. Then, a shape-remodeling group sparse constraint algorithm is proposed and combined with the particle swarm optimization method to simultaneously reconstruct the unknown layout and targets. Compared to the conventional compressed sensing-based methods, the proposed method integrates the basic structural characteristics and sparsity prior of the NLOS image to improve the stability of the solution. Finally, the performance of the proposed method is verified with numerical and experimental results.

Propagation Characteristics of Acoustic Emission Signals in Stiffened Cylindrical Shells Based on the Multipath Propagation Model

A stiffener attached to a cylindrical shell strongly interferes with the propagation of the acoustic emission (AE) signal from the fault source and reduces the fault detection accuracy. The interaction of AE signals with the stiffener on the cylindrical shell is thoroughly investigated in this paper. Based on the proposed model of the AE signal propagating inside the cylindrical shell with a stiffener, the installation constraints for the sensor are derived, resulting in the separation of the direct signal, the stiffener scattering signal, and other signals in the time domain. On this basis, combinations of the excitation frequency and the stiffener height are simulated, and the reflection and transmission of the AE signal in each case are quantitatively characterized by the scattering coefficients. The results indicate that there is a “T-shaped” transformation of the signal at the stiffener, which evolves into a variety of other modes. Moreover, the reflection and transmission coefficients of the incident AE signal are displayed as a function of the excitation frequency and the height of the stiffener. In addition, the accuracy of the scattering coefficients obtained from the numerical simulations is verified by experiments, and a good consistency between simulation results and experiment results is presented. This work illustrates the propagation characteristics of AE signals in a cylindrical shell with a stiffener, which can be used as guidance for optimizing the spatial arrangement of sensors in AE monitoring.

Underwater Ultrasonic Multipath Diffraction Model for Short Range Communication and Sensing Applications

In acoustic underwater communication and sonar applications, obstacles inside and outside the line-of-sight (LOS) affect signal propagation. Both reflection and diffraction occur in underwater communication and measurement systems due to these obstacles. To the best of our knowledge, the influence of diffraction and reflection is neither described nor modeled for finite pulses yet. We propose and develop a multipath propagation model for spectral diffraction components and phase information of the received signal based on knife-edge diffraction together with reflections, transmission effects, and backscatter. This paper designs a short range underwater ultrasonic experimental system composed of an ultrasonic transceiver with wideband pulses and advanced spectral signal processing. We evaluate our proposed model with measurements made in a water tank with an obstacle moved between the transmitter and receiver. When the model includes all major propagation components and effects, it achieves an accuracy for localization of 97% of the results in the range of twice the obstacle diameter in our test setup.

Research efficiency use of orthogonal double polarization MIMO antennas in drone communication

The article considers possible variants of application of various MIMO schemes for the communication with the drone or unmanned aerial vehicle. The model of multipath propagation of radio waves taking into account polarization parameters of antennas is given. The main focus is on the use of MIMO technology with polarization-orthogonal channels and channels with double polarization. The evaluation of the efficiency of using full polarization reception in comparison with MIMO channels of one polarization is given. Attention is paid to the presence of cross-polarization solution between the channels.

Optimal Deployment of Phased Array Antennas for RFID Network Planning Based on an Improved Chicken Swarm Optimization

Effective network planning improves performance in the radio-frequency identification (RFID) system. This article proposes an optimal deployment of phased array reader antennas for RFID network planning (RNP). For practical considerations, the RNP problem is analyzed and formulated based on a multipath propagation model, where each reader is equipped with a phased array antenna. The gains and radiation directions of the antennas are adjusted by voltage states instead of gestures, reducing the cumbersome antennas redeployment. An indicator called amplitude fluctuation under narrowband (AFN) is proposed to reflect the disturbance of frequency selective fading caused by the multipath effect. To effectively address the RNP problem, an improved chicken swarm optimization algorithm with two targeted strategies is developed. Simulation and experiment comparisons with the existing algorithms demonstrate the superiority of the proposed approach.

Multiple Targets Localization Behind L-Shaped Corner via UWB Radar

This paper deals with the multiple targets localization problem via multi-channel ultra-wideband (UWB) imaging radar non-line-of-sight (NLOS) signal processing. A novel matching-based radar imaging algorithm is proposed to obtain the positions of multiple targets in the L-shaped corner scenario with complex multipath ghost signals. Firstly, a multipath propagation model for the multiple targets scenario is established. Then the positions of the actual multipath ghosts are extracted from the radar image, and the candidate targets corresponding to these multipath ghosts are derived. Secondly, the ellipse-cross-localization method is proposed to obtain the positions of the candidate multipath ghosts, followed by two defined matching factors to measure the similarity between actual and candidate multipath ghosts. According to the similarity, decision rules are designed to determine the actual targets. Compared with the localization algorithm based on one-dimensional range profile, the proposed algorithm can effectively cope with the cases of multiple targets, even in the cases of rough walls and noise. Finally, simulations and experimental data are used to validate the effectiveness of the proposed algorithm.

Algorithm of Low-Flying Target Tracking in Monopulse Radar Stations Based on a Unscented Kalman Filter

Using the model of multipath propagation of radio waves and the method of unscented Kalman filtering, a nonlinear adaptive algorithm for tracking low-flying targets in a monopulse radar station has been developed. This algorithm, in contrast to the extended Kalman filter, makes it possible to compensate for significant autocorrelated interference in measurements of the elevation angle of low-flying targets, arising from reflections of radio waves from the underlying surface. The results of simulation of the proposed algorithm are presented.

Investigation of Deterministic, Statistical and Parametric NB-PLC Channel Modeling Techniques for Advanced Metering Infrastructure

This paper is focused on the channel modeling techniques for implementation of narrowband power line communication (NB-PLC) over medium voltage (MV) network for the purpose of advanced metering infrastructure (AMI). Three different types of models, based on deterministic method, statistical method, and network parameters based method are investigated in detail. Transmission line (TL) theory model is used to express the MV network as a two-port network to examine characteristics of sending and receiving NB-PLC signals. Multipath signal propagation model is used to incorporate the effect of multipath signals to determine the NB-PLC transfer function. A Simulink model is proposed which considers the values of MV network to examine the characteristics of NB-PLC signals. Frequency selectivity is also introduced in the impedances to compare variations and characteristics with constant impedances based MV network. A state-of-the-art mechanism for the modeling of capacitive coupling device, and impedances of low voltage (LV) and MV networks is developed. Moreover, a comparative analysis of TL theory and multipath signal propagation models with the proposed Simulink model is presented to validate the performance and accuracy of proposed model. This research work will pave the way to improve the efficiency of next-generation NB-PLC technologies.

The research on propagation characteristics of acoustic emission signals in stiffened plates based on the multipath propagation model

Mechanical equipment with the stiffener has a strong interference with the propagation of acoustic emission (AE) signals from faults, reducing the accuracy of fault detection. This paper conducts an in-depth study of the interaction between AE signals and the stiffener. The installation constraints, that can separate the direct signal, signals scattered from the stiffener and signals reflected from the boundary in the time domain, for sensors are deduced based on the multipath propagation model of AE signals in the stiffened plate. On this basis, the scattering characteristics of AE signals with different frequencies in different height stiffened plates are predicted by simulations. Moreover, the reflection and transmission coefficients are calculated to quantify the scattering characteristics. The results show that the signal, undergoing a “T-shaped” transformation at the stiffener, generates various modes, among which the transmission signal accounted for the largest proportion. In addition, experiments are performed to verify the numerical simulations, and the results are in good agreement with the numerical simulations. This work clarifies the propagation characteristics of AE signals in stiffened plates, and the research can optimize the spatial arrangement for sensors.

Design of Attenuation loss and Multipath propagation Model for Underwater Acoustic Communication in Tank

The wireless sensor network uses some sort of sensors to detect in general physical quantity of interest. The wireless sensor network has potential to explore difficult-to access area on the earth and the concept is extended to underwater applications in future. Past several years studies has been focused on development of reliable and robust communication systems for underwater wireless sensor network for various underwater applications. The scenario of communication is different in underwater compared to that on land as environment is completely different. Also radio waves cannot propagate for longer distance, so instead of that acoustic waves are used. The efforts are made to devise a model for acoustic frequency ranges in the environment for underwater tanks using basic equations governing various physical phenomena occurring during acoustic wave propagation. The model uses scenario of underwater tank filled with raw water diluted with sodium chloride with communicating devices placed at various distances. Attenuation model can be proposed for such communication scenario with respect to distance between transmitter and receiver for acoustic frequency ranges. The acoustic wave travelling through propagating medium suffers from multiple reflections resulting into multipath propagation. The multipath propagation model is proposed for calculation of length of multipath signals propagating in bounded shallow water. Propagation delays of each multipath signals are proposed. Empirical relationship is developed between number of multipath components and distance between transmitter and receiver. Arrival time lag jitter of various multipath signals are developed with respect to distance between transmitter and receiver and height of transmitter and receiver with respect to water bottom is also proposed.

An edge computing framework based on OFDM radar for low grazing angle target tracking

In this paper, a novel adaptive algorithm to detect and track targets with low grazing angle is addressed. For this purpose, an orthogonal frequency division multiplexing (OFDM) radar signal is employed through an edge computing framework over the radar platform. However, detecting the targets in the low grazing angle area is a great challenge due to severe multipath reflection effects. The Earth’s curvature geometry model is presented as the multipath propagation model. Based on the fact that the different scattering centers of a target resonate at different frequencies, we use the optimized OFDM waveform and propose a novel target tracking procedure for low grazing angle target tracking scenarios. The obtained results show that using an OFDM radar waveform provides a more uniform detection coverage in the presence of multipath propagation such that this will fill in the nulls. Finally, simulations are used to compare the performance of the proposed OFDM waveform with the conventional equal-power, the generalized likelihood ratio (GLR)-based and single-carrier waveforms.

Iterative Sparse Channel Estimation and Spatial Correlation Learning for Multichannel Acoustic OFDM Systems

This article addresses the problem of coherent detection of acoustic orthogonal frequency division multiplexing (OFDM) signals using a sparse channel estimation method based on a physical model of multipath propagation. Unlike the conventional sample-spaced and subsample-spaced methods, such as least squares and orthogonal matching pursuit (OMP), which target the taps of an equivalent discrete-delay channel response, the path identification (PI) method targets the physical propagation paths in a continuous-delay domain, and focuses on explicit estimation of delays and complex amplitudes of the channel paths in an iterative fashion. When multiple receive elements are available, two situations are possible: one in which the array elements see uncorrelated channel responses, and another in which the channel responses are correlated. In the first case, channel estimation must be accomplished element-by-element. This is done simply by applying the PI algorithm to each element individually. In the second case, correlation between the elements can be exploited. In doing so, our goal is to reduce the signal processing complexity without compromising the performance. Toward this goal, an adaptive precombining method is proposed. Without requiring any a priori knowledge about the spatial distribution of received signals, the method exploits spatial coherence between receive channels by linearly combining them into fewer output channels so as to reduce the number of subsequent channel estimators. The algorithm learns the spatial coherence pattern recursively over the carriers, thus effectively achieving broadband beamforming. The reduced-complexity precombining method relies on differential encoding that keeps the receiver complexity at a minimum and requires a very low pilot overhead. Using synthetic data as well as 210 experimental signals transmitted over a 3–7-km shallow-water channel in the 10.5–15.5-kHz acoustic band during a 3.5-h experiment, we study the system performance in terms of data detection mean-squared error (MSE), symbol error rate, and bit error rate (BER), and show that the PI algorithm achieves excellent MSE performance while its complexity is considerably lower than that of the OMP algorithm. We also demonstrate that the receiver equipped with the proposed reduced-complexity precombining scheme requires three times fewer channel estimators while achieving the same MSE and BER performance as the full-complexity receiver.