Multipath Signal Propagation Research Articles

Enhancing Underwater Acoustic Target Recognition Through Advanced Feature Fusion and Deep Learning

Underwater Acoustic Target Recognition (UATR) is critical to maritime traffic management and ocean monitoring. However, underwater acoustic analysis is fraught with difficulties. The underwater environment is highly complex, with ambient noise, variable water conditions (such as temperature and salinity), and multi-path propagation of acoustic signals. These factors make it challenging to accurately acquire and analyze target features. Traditional UATR methods struggle with feature fusion representations and model generalization. This study introduces a novel high-dimensional feature fusion method, CM3F, grounded in signal analysis and brain-like features, and integrates it with the Boundary-Aware Hybrid Transformer Network (BAHTNet), a deep-learning architecture tailored for UATR. BAHTNet comprises CBCARM and XCAT modules, leveraging a Kan network for classification and a large-margin aware focal (LMF) loss function for predictive losses. Experimental results on real-world datasets demonstrate the model’s robust generalization capabilities, achieving 99.8% accuracy on the ShipsEar dataset and 94.57% accuracy on the Deepship dataset. These findings underscore the potential of BAHTNet to significantly improve UATR performance.

A Line of Sight/Non Line of Sight Recognition Method Based on the Dynamic Multi-Level Optimization of Comprehensive Features.

With the advent of the 5G era, high-precision localization based on mobile communication networks has become a research hotspot, playing an important role in indoor emergency rescue in shopping malls, smart factory management and tracking, as well as precision marketing. However, in complex environments, non-line-of-sight (NLOS) propagation reduces the measurement accuracy of 5G signals, causing large deviations in position solving. In order to obtain high-precision position information, it is necessary to recognize the propagation state of the signal before distance measurement or angle measurement. In this paper, we propose a dynamic multi-level optimization of comprehensive features (DMOCF) network model for line-of-sight (LOS)/NLOS identification. The DMOCF model improves the expression ability of the deep model by adding a res2 module to the time delay neural network (TDNN), so that fine-grained feature information such as weak reflections or noise in the signal can be deeply understood by the model, enabling the network to realize layer-level feature processing by adding Squeeze and Excitation (SE) blocks with adaptive weight adjustment for each layer. A mamba module with position coding is added to each layer to capture the local patterns of wireless signals under complex propagation phenomena by extracting local features, enabling the model to understand the evolution of signals over time in a deeper way. In addition, this paper proposes an improved sand cat search algorithm for network parameter search, which improves search efficiency and search accuracy. Overall, this new network architecture combines the capabilities of local feature extraction, global feature preservation, and time series modeling, resulting in superior performance in the 5G channel impulse response (CIR) signal classification task, improving the accuracy of the model and accurately identifying the key characteristics of multipath signal propagation. Experimental results show that the NLOS/LOS recognition method proposed in this paper has higher accuracy than other deep learning methods.

Machine Learning Based Localization of LoRa Mobile Wireless Nodes Using a Novel Sectorization Method

Indoor localization of wireless nodes is a relevant task for wireless sensor networks with mobile nodes using mobile robots. Despite the fact that outdoor localization is successfully performed by Global Positioning System (GPS) technology, indoor environments face several challenges due to multipath signal propagation, reflections from walls and objects, along with noise and interference. This results in the need for the development of new localization techniques. In this paper, Long-Range Wide-Area Network (LoRaWAN) technology is employed to address localization problems. A novel approach is proposed, based on the preliminary division of the room into sectors using a Received Signal Strength Indicator (RSSI) fingerprinting technique combined with machine learning (ML). Among various ML methods, the Gated Recurrent Unit (GRU) model reached the most accurate results, achieving localization accuracies of 94.54%, 91.02%, and 85.12% across three scenarios with a division into 256 sectors. Analysis of the cumulative error distribution function revealed the average localization error of 0.384 m, while the mean absolute error reached 0.246 m. These results demonstrate that the proposed sectorization method effectively mitigates the effects of noise and nonlinear signal propagation, ensuring precise localization of mobile nodes indoors.

Risks of Multipath Signal Propagation From GPS Satellites in Mountainous Areas During the Use of UAV as Supplementary Device for HEMS or SAR

It cannot be disputed that using unmanned aerial vehicles as a supplementary search and rescue component is still increasingly being discussed. Several approaches to solving the problem can be stated - buying specially designed unmanned aerial vehicles for HEMS (Helicopter Emergency Medical Service)/SAR (Search and Rescue) or modifying conventional UAVs to supplementary devices for HEMS or SAR. Regardless of which alternative the end-user prefers, the navigation method and determining the current position in space stays unchanged - primarily, the navigation signals from GNSS (Global Navigation Satellite Systems) satellites are used. However, this method can be loaded by the error caused by environmental conditions in which the rescue UAV moves, such as mountains, valleys, specific flora, trees, and much more. All of that causes attenuation, loss or multipath propagation of the signal. In the case of the remote-controlled flight of the UAV (by a pilot-operator or operator itself from the ground station) and when the rule of direct visibility (Visual Line of Sight - VLOS) is used for an unmanned aerial vehicle, this may not be a considerable problem. However, during an automated or fully autonomous flight and the flight of an unmanned aerial vehicle beyond direct visibility (Beyond Visual Line of Sight - BVLOS), knowledge about the exact position of the UAV in space is crucial. The presented article is dedicated to verify the claim about the significance of the problem of multipath signal propagation from the GPS (Global Positioning System) satellite in a selected mountain area, The Little Cold Valley in High Tatras, Slovak Republic.

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.

Online Learning-Based Adaptive Device-Free Localization in Time-Varying Indoor Environment

With the widespread use of WiFi devices and the availability of channel state information (CSI), CSI-based device-free localization (DFL) has attracted lots of attention. Fingerprint-based localization methods are the primary solutions for DFL, but they are faced with the fingerprint similarity problem due to the complex environment and low bandwidth of the commercial WiFi. Meanwhile, fingerprints may change unpredictably due to multipath WiFi signal propagation in time-varying environments. To tackle these problems, this paper proposes an adaptive online learning DFL method, which adaptively updates the localization model to ensure long-term accuracy and adaptability. Specifically, the CSI signals of the target located at different reference points are first collected and transformed to discriminable fingerprints using the weights of Multilayer Online Sequence Extreme Learning Machine (ML-OSELM). After that, an online learning DFL model is built to adapt to the changes of the environment. Experimental results in a time-varying indoor environment validate the adaptability of the proposed method against environmental changes and show that our method can achieve 10% improvement over other methods.

Интервально-импульсная модуляция сверхширокополосных хаотических радиоимпульсов: теория и эксперимент

An approach to reduce the negative impact of multipath signal propagation (interpulse interference) in a wireless communication channel has been proposed. Pulse-interval modulation of chaotic radio pulses allows to increase the time interval between pulses without reducing the average bitrate. The possibility of using this method in ultra-wideband microwave channels with multipath propagation is demonstrated. The noise immunity of the AWGN channel has been studied. An experimental implementation of the method is described.

An effective method for modelling wireless communication systems

Statement of the problem. To describe the multipath propagation of radio signals using two models: the ray tracing method and the method of stochastic simulation. Let us consider the stochastic model as the most general one that allows to describe various scenarios and factors influencing signal propagation such as multipath, arrival time variance, distance loss, atmospheric conditions, etc. Under real-world conditions, channel variation does not follow a Gaussian distribution. Coloured non-Gaussian noise has to be taken into account in the design and modelling of the wireless communication system. The complexity of the stochastic channel modelling method is that the variation of PSD power spectral density function and PDF probability density function of a random variable are strongly related to each other. To remove the limitations of existing methods, the Gaussian random variable filtering method is used. But in contrast to the applied simulation techniques, we will use Global Search Optimization (GSE) algorithm. Objective. To investigate a possibility of generation of colored non-Gaussian noise which satisfies the specified requirements by the filtering method based on the global search optimization algorithm. Results. The method based on the global search optimization algorithm for generating colored non-Gaussian noise, which satisfies specified requirements of the Spectral Power Density function and the Probability Density function, is proposed. Numerical simulation results confirm its effectiveness. The advantage of the new method is that the complexity of calculating the required pre-distortion for the filter is replaced by a simple search method. Once the required coefficients are found, non-Gaussian noise generation can be accomplished by secondary filtering and inverse transform. Practical Significance. Compared to methods based on block structures or other analytical methods, the proposed method is more suitable for real-time wireless channel simulation.

Detection of Echo Signals Taking Into Account the Multipath Effect of the Waveguide and the Multispecularity of the Reflector

In the shelf zone, an experimental study was conducted on the possibility of increasing the probability of detecting echo signals against an noise background as a result of taking into account the multipath waveguide model and design features of the reflector. The possibility of increasing the tracking range and reducing the probability of false alarms is experimentally substantiated with an algorithm that uses the duration of the time interval during which a sequence of signals reflected from one reflector is observed due to the multipath propagation of signals and multispecularity of the reflected signal, if the target structure is complex and includes several offset reflectors. Recommendations are given on the choice of intervals, the sampling lengths within which summation of the energy of the reflected signals is possible. It is shown that as a result of signal power accumulation using an algorithm that partially takes into account the echo signal model, the target tracking time increases and false alarms decrease.

Analytical model OFDM-MIMO signal in a radio channel with frequency-time selective fading

One of the main problems in modern wireless electronic communication networks is the transmission and reception of signals in multipath propagation. Due to the imperfect impulse response of the communication channel, frequency-selective fading of the transmitted signal occurs. This can cause waveform distortion and inter-symbol interference, which can seriously degrade the performance of the communication system. Thus, increasing the noise immunity of wireless electronic communication networks in real-world conditions is one of the most important tasks of modern communication technologies. Orthogonal frequency division multiplexing is known for its resistance to multipath fading and is used to reduce the impact of inter-symbol interference. Multi-antenna systems are a key technology for increasing bandwidth and improving communication reliability. The combination of these two technologies in wireless electronic communication networks can reduce the impact of negative phenomena on the transmitted signal in difficult interference conditions. An analytical model of the signal transmitted by a nonstationary frequency-selective radio channel in a wireless electronic communication network with orthogonal frequency multiplexing and a multi-antenna system is proposed. Analytical expressions are presented that allow us to jointly take into account the influence of interchannel and inter-symbol interference (the effect of multipath signal propagation and Doppler shift on the transmitted signal) against the background of fluctuating noise. Taking into account the factors affecting the transmitted signal makes it possible to bring the model closer to the real processes that occur in the vast majority of radio channels of wireless electronic communication networks.

Common-Mode Clutter Filtering for the Problem of Sounding Multilayer Media Using Ground-Penetrating Radar

Eliminating common-mode clutter in data is one of the key aspects of road sensing with GPR. Common-mode interference can occur as a result of multipath propagation of an electromagnetic signal when the reflected signal from the same object arrives at the receiver from different directions and with different delays. Similar phenomena also occur when using antennas raised above the surface due to multiple reflections between the air–surface interface and the antenna. These interferences can significantly distort the data received by the GPR and interfere with the accurate determination of the parameters of the roadway. Therefore, the elimination of common-mode clutter is an important task to improve the quality of the obtained results. In this paper, we consider a method for filtering common-mode clutter in the radar data of the multichannel GPR “Terrazond”, which were obtained by sounding a test section of a highway. The results obtained during filtering can then be used to determine the thickness of the pavement layers using approaches that take into account the signal delay determined by the amplitude jump, for example, the common point method or if the permittivity of each layer is known. The obtained thicknesses of pavement layers are compared with the results obtained during core drilling by the Russian Road Research Institute.

Minimizing the Destructive Effects of Multipath Signal Propagation on Wireless Radio Signal

Minimizing the Destructive Effects of Multipath Signal Propagation on Wireless Radio Signal

The Statistical Analysis of the Security for a Wireless Communication System with a Beaulieu-Xie Shadowed Fading Model Channel

The paper considers the problem of a wireless communication system’s physical level security for a multipath signal propagation channel and the presence of a wiretap channel. To generalize the propagation effects, the Beaulieu-Xie shadowed channel model was assumed. To describe the security of the information transfer process, such a metric as the secure outage probability of was considered. An analytical expression of the secure outage probability was obtained and analyzed depending on the characteristics of the channel and the communication system: the average value of the signal-to-noise ratio in the main channel and the wiretap channel, the effective path-loss exponent, the relative distance between the legitimate receiver and the wiretap and the threshold bandwidth, normalized to the bandwidth of a smooth Gaussian channel. The analysis considers the sets of parameters that cover all practically important scenarios for the functioning of a wireless communication systems: both deep fading (corresponding to the hyper-Rayleigh scenario) and small fading, both in the case of a significant line-of-sight component and a significant number of multipath clusters, and with significant shadowing of the dominant component and a small number of multipath waves, as well as all intermediate options. It is found out that the value of the energy requirements for guaranteed secure communication at a given speed is determined primarily by the power of multipath components, as well as the existence of an irreducible secure outage probability of a communication session with an increase for channels with strong overall shadowing of the signal components, which from a practical point of view is important to take into account when imposing requirements for the values of the signal-to-noise ratio and the data transfer rate in the direct channel, providing the desired degree of security of the wireless communication session.

Асимптотически робастный инвариантный алгоритм демодуляции DPSK-сигналов при воздействии внешних помех с априорно неопределенными параметрами

The study aims at synthesizing an asymptotically robust invariant demodulation algorithm for DPSK signals with arbitrary modulation multiplicity used in aircraft communication systems and observed against the background of noise with an unknown probability distribution and a noise complex with a priori uncertain parameters. The analysis of the efficiency of the proposed algorithm is carried out by a computer simulation modeling. The algorithm implies automatic detection and rejection of narrowband pulse noise. This type of interference is typical for radio-navigation systems. It has been shown that the narrowband pulse noise should be eliminated if the signal-to-interference ratio becomes less than -10 dB. The use of the asymptotic robustness principle ensures the stability of the algorithm characteristics to changes in the character of the noise probability distribution density. It was found that the joint application of narrowband pulse interference elimination and the asymptotically robust approach provides reliable demodulation performance both when receiving against the background Gaussian noise and under the action of pulse interference and noise with "heavy tails". In addition, it has been shown that the use of signals with differential phase modulation, direct sequence spread spectrum, and the sidelobe levels of less than 10% effectively suppresses interference caused by multipath signal propagation.

Theoretical Analysis of Adaptive Algorithm Modulation Scheme in 3D OFDM WiMAX System

The growth of wireless networking has contributed to the need for high-speed services and multimedia applications anywhere and at any time. OFDM WiMAX technology is now considered one of the most popular technologies capable of delivering faster implementation and lower cost than standard wired options for Broadband Wireless Connectivity in metropolitan areas. This paper proposes appropriate adaptive modulation to be used in wireless networks based on SISO and MIMO OFDM WiMAX, which allows the performance of the network to be improved in the case of non-line-of-sight communications that are typical in urban environments. The effects of several paths, signal attenuation, Doppler shift, and different mobility speeds on the performance of the system were investigated. Mathematical models analysis of adaptive modulation in SISO and MIMO systems is treated by using BER, SNR and noise components. Simulation results show that the adaptive algorithm would improve throughput. It can also be concluded that when processing signals in a receiving system under conditions of multi-path signal propagation, the use of adaptive algorithms has a positive effect on noise immunity.
 HIGHLIGHTS
 
 With the growing evolution of wireless communication technologies, there is still a need for higher data rates, increased system capacity, and improved service quality
 3D OFDM-MIMO WiMAX technology is now regarded as one of the most common solutions for Broadband Wireless Connectivity in Urban Areas, capable of offering faster implementation and lower costs than standard wired options
 Effective adaptive algorithm processing in 3D wireless networks based on SISO-OFDM and MIMO-OFDM WiMAX was proposed, enabling network performance to be enhanced in the case of non-LOS wireless communications, which are standard in urban conditions. On the performance of the system, signal attenuation, the effects of several paths, different mobility speeds and Doppler shift were studied
 The adaptive algorithm significantly reduces the probability of error and increases the throughput. It can be concluded that the use of adaptive spatio-temporal algorithms has a positive effect on noise immunity when processing signals in the receiving system under conditions of multipath signal propagation
 
 GRAPHICAL ABSTRACT

Implementation of FBMCbased Massive MIMOusing Space Time Block Coding

In wireless communication multipath propagation of signal will cause major drawbacks like Intersymbol interference (ISI), Delay spread, Doppler Spread and Intercarrier interference. These drawbacks are efficiently handled by using OFDM technology with Cyclic Prefix, but at the cost of High PAPR increasing the non-linear behaviour of Power Amplifier thereby increases BER and inband distortion, high out of band emissions and loss of spectral efficiency.To reduce the PAPR several PAPR reduction techniques have been proposed over the last few decades but at high complexity. Due to above drawbacks, OFDM technology is not able to provide the requirements of next generation wireless communication and thereby making it un-favourable for 5G communications. To overcome above drawbacks of OFDM, I used a, Filter Bank multicarrier (FBMC), 5G candidate waveform and proposed a method for reducing PAPR, Out-of-band emissions and latency with improving spectral efficiency. I developed a novel precoding method based on a pruned Discrete Fourier Transform (pDFT) in combination with Poly Phase Network (PPN) architecture. The proposed technique has the same peak-to average power ratio as OFDM but does not require a cyclic-prefix and has much lower out-of-band emissions. Furthermore, my method restores complex orthogonality and the ramp-up and ramp-down period of FBMC is dramatically decreased, allowing low latency transmissions. PPN is processed after pDFT, which transforms the received data into ISI-free data.

Локальное местоопределение приемника связи и проблема многолучевости в сложных условиях

In conditions when the signals of satellite navigation systems are unavailable or distorted, the receiver positioning task could be solved by local positioning system with an integrated data transmission channel. However, when such a system operates in various environments, a lot of multipath signals might appear, which strongly distort delay and phase measurements, on the basis of which the receiver coordinates are calculated. The accuracy of measurements can be significantly increased by introducing measurement redundancy by using the signal reflection properties and increasing the tracking channels on the receiver. In this article, a technique is proposed for creating and using the redundancy of phase measurements, as well as the phase derivatives differences of the local positioning system signals. This technique is based on the effects of signal reflection. An algorithm is proposed for estimating the intensity of the relative acceleration of a moving object, which makes it possible, using the threshold method, to switch between receiver channels at the moments when abnormal spikes appears because of the influence of a multipath signal propagation channel. An algorithm for smoothing transitions between antennas is also proposed using cubic spline interpolation. The obtained methods and algorithms, using two receiving antennas with a single phase center, make it possible to exclude about 80% of spikes caused by multipath effects from estimates of the relative velocity of a moving object, and also provide a basis for developing more advanced methods for using redundancy and further research in this area.

Multipath Propagation of Acoustic Signal in a Swimming Pool-Source Localization Problem.

This paper explores the problem of severe multipath propagation of underwater acoustic signals in a swimming pool. The problem appeared in a study that examined a system used to signal emergency situations (i.e., pre-drowning symptoms detected by a wearable device on a pool user’s wrist) and locate the signal source. A swimming pool acoustic environment is characterized by the presence of large flat reflecting planes surrounding a small volume of water. The reflections are numerous and much stronger than in typical hydroacoustic applications. In this paper, we attempted to create a model of the swimming pool response, one that is suitable for simulation experiments with detection and localization of emergency signals. Then, we explore the possible remedies for the localization system, applied on the transmit side (waveform design) and on the receive side (receiver placement and signal processing). Finally, we present an algorithm for object localization, considering the possible reflections with a multi-hypothesis approach.

Анализ передачи дискретных сообщений в системах мультиплексирования с ортогональным частотным разделением каналов

High data transfer rates are required in modern digital radio transmission systems. But an increase in the data transfer rate leads to a deterioration in the transmission quality and a high BER (bit error rate). OFDM technology, which was introduced in the 1960s, implements all these functions. In this paper, the influence of fading channels on the transmission of information in OFDM systems is investigated. In wireless systems for transmitting discrete messages, the channel parameters greatly affect the transmission quality, as interference, noise and fading affect the useful signal. Fading is a very common phenomenon in wireless communication systems, affecting the phase shift of the signal. In an urban environment, multipath propagation of signals also takes place, since signals propagate along two or more paths before reaching the receiver. Depending on the signal propagation medium and communication conditions, small-scale fading can be distinguished. At the same time, there are significant changes in the amplitude and phase of the signal. Small-scale fading occurs on a smaller scale, comparable to the wavelength of the transmitted signal, and often changes throughout the signal path, and may change one or more times during the transmission time of the symbol, which leads to so-called flat (smooth) and frequency-selective fading. The results obtained show the effect of fading on the digital transmission system (OFDM). The three discrete message delay profiles used represent a low-, medium-, and high-latency propagation environment, respectively. A model of a wireless digital communication system (OFDM) has been built using the SystemVue software.

ДВУХСТУПЕНЧАТЫЙ АЛГОРИТМ СОГЛАСОВАННОЙ ФИЛЬТРАЦИИ СИГНАЛОВ

Introduction. Introduction. To combat inter-symbol interference resulting from multipath signal propagation, spreading of the signal frequency spectrum, channel equalizing, OFDM-multiplexing with orthogonal frequency division of channels is used. To reduce the influence of non-linear signal distortions, methods of pre-distortion, diversity reception, as well as special algorithms for digital processing of the demodulator output signal are used. The effect of additive noise is reduced by using a filter matched to the signal. Objective. It is advisable to develop a matched filtering algorithm that allows one to simultaneously reduce the influence of additive noise, non-linear signal distortions and its multipath propagation on the correct message reception. The idea of selecting the orthogonality weight can also be used to achieve the goal. Result. To reduce the influence of non-linear distortions on the correct reception of a message under conditions of multipath signal propagation and additive interference, it is proposed to use two stages of signal processing. The first step is to minimize the noise dispersion caused by intersymbol interference and non-linear signal distortions. The specified dispersion is minimized by determining the orthogonality weight of the basis-functions that make up the signal. The second step is to use a classic matched filter. The proposed two-stage matched filtering algorithm makes it possible to simultaneously reduce the influence of non-linear distortions, intersymbol interference resulting from multipath propagation, and additive interference on the correct signal reception. Signals distorted and delayed in time relative to the main signal are proposed to be considered as additive interference.