Presence Of Multipath Propagation Research Articles

Direction Finding for Passive Bistatic Radar in the Presence of Multipath Propagation

In the case of multipath propagation for passive bistatic radar (PBR) using uncooperative frequency agile-phased array radar as an illuminator, a new direction-finding method is proposed to deal with the scenario where the coherent and uncorrelated signals are closely spaced or in the same direction. Firstly, spatial difference technique is used to eliminate uncorrelated signals. Then, in order to avoid the cross-terms effect and improve the resolution of coherent signal, the iterative adaptive method (IAA) is adopted for the rearranged spatial difference matrix. Finally, the direction of arrival (DOA) of the target signal is obtained by the reconstruction of the interference-plus-noise covariance matrix. Compared with previous studies, this method has better performance in the case of low signal-to-noise ratio (SNR) and limited number of snapshots.

РАЗРАБОТКА АДАПТИВНОЙ СИСТЕМЫ СВЯЗИ НА ОСНОВЕ OFDM ДЛЯ ТРОПОСФЕРНОГО И РАДИОРЕЛЕЙНОГО КАНАЛА

It is known that inter-symbol interference may occur during data transmission in radio relayand tropospheric communication systems. The presence of multipath propagation, frequencyselectivefading and extreme instability in the tropospheric and radio relay channel significantlyreduces the energy efficiency of the communication system. The aim of the work was to increasethe efficiency of using the channel for radio relay and tropospheric communication by usingOFDM (orthogonal frequency-division multiplexing) signals in the system using adaptive codingand modulation. In the course of execution, the modulator and demodulator models of the OFDMsignal are implemented. When using various signal code structures in various reception/transmission conditions, it is possible to achieve optimal use of the frequency and energyresources, to create systems that adapt to the conditions of signal propagation. To implement thismechanism, a service field was introduced into the transmitted service data, which contains informationabout the code rate used, the modulation type, and the interleaving depth. This approachallows optimizing the use of energy and frequency resources. Together with the use of channelquality estimation algorithms, it becomes possible to dynamically change the signal-code structurewhen the reception conditions change. By adjusting the interleaving depth, it is possible to optimizethe S/N threshold or the amount of information delay in the channel, depending on the systemrequirements. The use of adaptive choice of code rate and modulation will allow more efficient useof the channel resource with a constant change in its state. The obtained results will significantlyincrease the energy efficiency of the OFDM system, lead to stable communication in nonstationarychannels and increase the throughput.

РАЗРАБОТКА ЭНЕРГЕТИЧЕСКИ ЭФФЕКТИВНОЙ СИСТЕМЫ СВЯЗИ В ТРОПОСФЕРНОМ РАДИОКАНАЛЕ НА БАЗЕ OFDM-СИГНАЛОВ

It is known that inter-symbol interference may occur during data transmission in radio relayand tropospheric communication systems. The presence of multipath propagation and frequencyselectivefading in the tropospheric, radio relay channel significantly reduces the energy efficiencyof the communication system as a whole. The aim of the work was to increase the efficiency ofusing the channel for radio relay and tropospheric communication by using OFDM (orthogonalfrequency-division multiplexing using the methods of reducing the peak factor of the OFDM signaland increasing the linearity of the transmission path. To evaluate digital predistortion algorithmsin the Matlab/Simulink environment, a model was developed for the LMS, NLMS, RLS, RPEMmethods and a power amplifier model with real characteristics. Based on the results of modelingalgorithms, RLS was chosen. In addition, in this work, a modified version of the adaptation algorithmbased on the recursive least squares method (RLSm) was developed. The main result of themodification is: a decrease in the number of arithmetic operations per iteration (more than5 times), an increase in the stability of adaptation algorithms, due to the introduction of regularizationmethods, a decrease in the convergence time, due to the introduction of an exponential dependence.Various algorithms for reducing the peak factor of an OFDM signal were investigated,the best result was achieved by combining Tone reservation (TR) and Active constellation extension(ACE). Simulation in the Matlab/Simulink environment showed that the combination of TRand ACE algorithms reduces the peak factor of OFDM signals by ~5dB for BPSK data stream and~4.5dB for 8-PSK, QAM-16, QAM-64, QAM-128 and QAM- 256. To increase the linearity of thetransmission path, the RLSm digital pre-distortion algorithm was selected and upgraded, it madeit possible to reduce the magnitude of the error vector modulus (EVM) by 13.5dB, and also increasethe modulation/error ratio (MER) by 13.6dB.

Frequency-Diversity-Based Underwater Acoustic Passive Localization

This article considers underwater acoustic passive localization of a noncooperative broadband source in the presence of multipath propagation. A differential transmission-loss model-based passive localization method is proposed, in which 3-D localization can be implemented with only two hydrophones. Instead of spatial diversity, frequency diversity is exploited to achieve passive localization with a limited number of hydrophones and address the challenge of multipath propagation. Specifically, the received signals of both hydrophones are decomposed in the frequency domain, respectively, at first. Then, a set of differential transmission-loss model-based equations between the two hydrophones are established on multiple frequencies. Based on these equations, the passive localization is modeled as a multivariate optimization problem. Meanwhile, the nonline of sight (NLOS)-related parameters are also involved in the optimization problem. Therefore, accurate localization and NLOS mitigation can be accomplished simultaneously by solving the optimization problem. To simplify the multivariate optimization problem for a reliable solution, a cepstrum-autocorrelation-based multipath estimation algorithm is proposed, by which all the NLOS paths can be represented by an equivalent NLOS path. Consequently, the simplified optimization problem concerns only the desired coordinate of the source and a single NLOS-related parameter. Finally, a differential evolution algorithm is employed to solve the simplified optimization problem. Both simulation and lake trial results corroborate the effectiveness and the robustness of the proposed method.

Smartphone User Tracking by Incorporating User Orientation Using a Double-Layer HMM

We consider the problem of localizing a smartphone user using received signal strength (RSS) measured by a set of known network nodes in a harsh indoor environment. While the RSS of a wireless signal can be conveniently accessed, using it to estimate location is non-trivial in the presence of multipath propagation, shadowing and radio interference. Auxiliary information, such as the indoor building map and user's orientation information, potentially can help to improve localization performance. As the indoor layout is usually known as a priori, a user's moving direction or orientation in a given indoor map may contain valuable information to assist for reducing location ambiguities at estimation, typically when the radio signal channel is corrupted with noise. In this paper, we propose a double-layer hidden Markov model (DHMM) within a Bayesian learning framework for combining user orientation information and processing RSS data in the localization process to deal with RSS fluctuations induced by human body shadowing and multipath interference. Simulation and experimental results show that incorporating user orientation can potentially provide promising indoor positioning results.

Single-Site 3-D Positioning in Multipath Environments Using DOA-Delay Measurements

Localization of a source signal in the presence of multipath propagation is addressed in this letter. This problem is often encountered in environments such as urban areas and indoor corridors. A 3-D positioning algorithm is presented. It uses the azimuth direction-of-arrival (azimuth-DOA), elevation-DOA and time-of-arrival (TOA) data, measured by a base station (BS). By applying virtual station (VS) technique, the non-line-of-sight (NLOS) paths, caused by multipath reflection, are converted into line-of-sight (LOS) paths. After that, a two-step weighted least squares (WLS) 3-D positioning algorithm is derived. Performance analysis is conducted by comparing the algorithm’s mean-squared-error (MSE) and the optimal Cramér-Rao bound (CRB). Simulation results are finally provided to verify the mathematical analysis.

Spectrally compatible aperiodic sequence set design with low cross- and auto-correlation PSL

It is known that unimodular sequence set with low cross- and auto-correlation peak sidelobe level (C/A-PSL) can improve the detection ability of the signal-of-interest in the presence of multipath propagation and/or clutters, while that with specified spectral power null/notch in certain frequency bands can prevent mutual interference of the systems that are operating in the same frequency bands. However, it is exceedingly difficult to design such a unimodular sequence set because nonsmooth quadratic objective function as well as nonlinear unimodular and spectral constraints are involved. In this paper, under the unimodular and spectral constraints, we formulate the sequence set design problem based on minimum C/A-PSL. Then, we apply block successive upper-bound minimization to solve the corresponding NP-hard problem and use the relation of the sequence auto-correlation and its fast Fourier transform (FFT) and inverse FFT to devise an efficient algorithm. Numerical examples show that the proposed method can effectively produce spectrally constrained sequence set with low C/A-PSL.

Simultaneous Model and Parameter Estimation for Joint Communication and Positioning

Joint communication and positioning based on a unified signal structure yields synergy and can complement and assist system designs enabling higher coverage and quality of service for both communication and positioning. For the time of arrival (TOA) based joint communication and positioning the TOA estimation accuracy is crucial. It is known to translate directly into position estimation accuracy. In the presence of multipath propagation, the estimation accuracy of signal arrival times in return strongly depends on the actual as well as the estimated number of the physical path parameters, the model order. In this work, we assess the performance and the mutual impact of simultaneous model order and parameter estimation for channel-estimation-based joint communication and positioning. Besides introducing a terrestrial channel-estimation-based unified joint communication and positioning system framework, we discuss and numerically compare different methods to sequentially or jointly estimate the parameters and the model order. We show that a TOA error-minimizing model order estimation is preferable over estimating the correct model order. Furthermore, we compare the performance with a proposed focused order-related lower bound. This bound determines the optimal model order for a chosen estimator. It depends on the actual and hypothetical model order and it replaces the here unsuitable Cramer-Rao lower bound. Secondly, the comparison shows that employing the parameter and model order-dependent inverse Fisher information matrix yields a close-to-optimal approach. We numerically show for a realistic channel scenario with many multipath parameters that the method is still accurate.

Joint Measurement of the Frequency and Temporary Shift of a Wideband Signal in Near Location Systems

Abstract—A method is presented for determining the frequency and time shifts of a phase-shifted pseudorandom signal in the presence of multipath propagation and Doppler deformation. It is based on postdetector calculation of the cross-ambiguity function according to a two-stage correlation-spectral scheme, when time delays are determined by calculating the cross-correlation function (CCF) of the received and reference signals replicating the law of modulation; the frequency shifts are determined from the spectral characteristics of CCF variations as a function of the time shift. The calculation algorithm is designed for real-time operation and implementation via programmable logic.

Modulation recognition in maritime multipath channels: A blind equalization-aided deep learning approach

Modulation recognition has been long investigated in the literature, however, the performance could be severely degraded in multipath fading channels especially for high-order Quadrature Amplitude Modulation (QAM) signals. This could be a critical problem in the broadband maritime wireless communications, where various propagation paths with large differences in the time of arrival are very likely to exist. Specifically, multiple paths may stem from the direct path, the reflection paths from the rough sea surface, and the refraction paths from the atmospheric duct, respectively. To address this issue, we propose a novel blind equalization-aided deep learning (DL) approach to recognize QAM signals in the presence of multipath propagation. The proposed approach consists of two modules: A blind equalization module and a subsequent DL network which employs the structure of ResNet. With predefined searching step-sizes for the blind equalization algorithm, which are designed according to the set of modulation formats of interest, the DL network is trained and tested over various multipath channel parameter settings. It is shown that as compared to the conventional DL approaches without equalization, the proposed method can achieve an improvement in the recognition accuracy up to 30% in severe multipath scenarios, especially in the high SNR regime. Moreover, it efficiently reduces the number of training data that is required.

Unified Subspace Fitting Framework and Its Performance Analysis for Direct Position Determination in the Presence of Multipath Propagation

The cost functions and their performances of direct position determination (DPD) methods in the presence of multipath propagation are investigated. We first establish a general DPD (GDPD) model in the presence of multi-path propagation and point out that the existing cost functions cannot get the emitter positions correctly because of the singularity of the manifold matrix in a multipath propagation scenario. Eight cost functions are developed for the GDPD model and formulated in a unified subspace fitting (USF)-based framework, which provides insight into their algebraic and asymptotic relations. Moreover, we derive the closed-form expressions of the asymptotic distributions of the estimation errors, which are optimized by those cost functions. Besides, the optimal cost function for achieving an optimal asymptotic performance is derived based on the optimization theory. Finally, the numerical simulations and Cramer–Rao lower bound are provided to verify the analytical results and show that: 1) the cost functions which work well in the single-path DPD model cannot find the emitters correctly in a multipath scenario; 2) the signal subspace fitting cost functions and noise subspace fitting cost functions, which are proposed in this paper, find the emitters accurately in the multipath propagation scenarios; 3) the optimal-weighted-subspace-fitting cost function holds the best asymptotic performance under the USF framework; and 4) the asymptotic performance of a multiple dimension cost function is better than a 1D cost function.

Coherency structure exploitation in DOA estimation for non‐circular sources

This study addresses the problem of direction-of-arrival (DOA) estimation for non-circular (NC) sources in the presence of multipath propagation. Recent research reveals that the use of the association of incident signals, i.e. source association (SA), can provide a significant gain in reducing DOA estimation error, especially in the presence of multiple sources. Here, in order to make full use of both the properties of NC sources and the SA information, the multipath model with NC sources is studied, and then a simple combination algorithm is proposed to estimate the SA, based on which, the authors derive an iterative root estimator to refine a given coarse DOA estimation. Meanwhile, the stochastic Cramer-Rao bound taking these two factors into account is derived as well. The proposed method is search-free and maintains the array aperture which is up to twice of the physical array aperture. Numerical simulations have been provided to verify the effectiveness of the proposed method.

FDS-MIMO Radar Low-Altitude Beam Coverage Performance Analysis and Optimization

Detecting and tracking low-flying targets at low-grazing angles is a difficult task due to the possible beam split and radar blind area. To alleviate this issue, we propose a frequency diverse subaperturing multiple-input multiple-output (FDS-MIMO) radar with optimized low-altitude beam coverage performance. A specular echo model is first formulated in the presence of multipath propagation together with a closed-form expression for the joint transmit–receive beampattern. Then, a perturbational echo model is developed for anomalous terrain. Moreover, a notional multipath mitigation region concept is defined together with the corresponding boundary conditions. The FDS-MIMO radar beam coverage capability is evaluated by the low observability rate. Furthermore, the FDS-MIMO radar low-altitude beam coverage is improved according to the solutions of boundary conditions, and an adaptive frequency offset design strategy is proposed for the changing environment. Both theoretical analysis and numerical results demonstrate that the optimized FDS-MIMO radar outperforms conventional phased-array radar and MIMO radar in terms of low-altitude beam coverage performance.

Direct Position Determination of Unknown Signals in the Presence of Multipath Propagation.

A novel geolocation architecture, termed “Multiple Transponders and Multiple Receivers for Multiple Emitters Positioning System (MTRE)” is proposed in this paper. Existing Direct Position Determination (DPD) methods take advantage of a rather simple channel assumption (line of sight channels with complex path attenuations) and a simplified MUltiple SIgnal Classification (MUSIC) algorithm cost function to avoid the high dimension searching. We point out that the simplified assumption and cost function reduce the positioning accuracy because of the singularity of the array manifold in a multi-path environment. We present a DPD model for unknown signals in the presence of Multi-path Propagation (MP-DPD) in this paper. MP-DPD adds non-negative real path attenuation constraints to avoid the mistake caused by the singularity of the array manifold. The Multi-path Propagation MUSIC (MP-MUSIC) method and the Active Set Algorithm (ASA) are designed to reduce the dimension of searching. A Multi-path Propagation Maximum Likelihood (MP-ML) method is proposed in addition to overcome the limitation of MP-MUSIC in the sense of a time-sensitive application. An iterative algorithm and an approach of initial value setting are given to make the MP-ML time consumption acceptable. Numerical results validate the performances improvement of MP-MUSIC and MP-ML. A closed form of the Cramér–Rao Lower Bound (CRLB) is derived as a benchmark to evaluate the performances of MP-MUSIC and MP-ML.

Efficient DOA estimation of noncircular signals in the presence of multipath propagation

The noncircularity of uncorrelated signals can improve the performance of direction of arrival (DOA) estimation using antenna arrays. However, due to reflection from surfaces or malicious jamming, the received noncircular signals may be a mixture of uncorrelated and coherent components in practice, which has not been considered by existing algorithms. This paper addresses the issue of DOA estimation for noncircular signals under multipath fading in smart antenna systems, and a novel two-stage processing method is proposed accordingly. By expanding the signal subspace from augmented array output, the DOA estimates of uncorrelated sources are first obtained, and then the covariance matrix of uncorrelated signals is reconstructed and removed from that of the mixed signals afterwards. Secondly, a spatial smoothing technique is performed on a denoised covariance to restore rank deficiency in the covariance of the remaining coherent signals. The resultant algorithm can resolve more signals than array elements with higher accuracy and better classification of signal type than previous methods. Additionally, a new deterministic direction estimation Cramér–Rao lower bound (CRLB) is derived for the considered mixture model. Simulation results demonstrate the validity and efficiency of the proposed method.

Localization of Multiple Targets With Identical Radar Signatures in Multipath Environments With Correlated Blocking

This paper addresses the problem of localizing an unknown number of targets, all having the same radar signature, by a distributed MIMO radar consisting of single antenna transmitters and receivers that cannot determine directions of departure and arrival. Furthermore, we consider the presence of multipath propagation and the possible (correlated) blocking of the direct paths (going from the transmitter and reflecting off a target to the receiver). In its most general form, this problem can be cast as a Bayesian estimation problem where every multipath component is accounted for. However, when the environment map is unknown, this problem is ill-posed and hence, a tractable approximation is derived where only direct paths are accounted for. In particular, we take into account the correlated blocking by scatterers in the environment which appears as a prior term in the Bayesian estimation framework. A sub-optimal polynomial-time algorithm to solve the Bayesian multi-target localization problem with correlated blocking is proposed and its performance is evaluated using simulations. We found that when correlated blocking is severe, assuming the blocking events to be independent and having constant probability (as was done in previous papers) resulted in poor detection performance, with false alarms more likely to occur than detections.

多径条件下的乘性阵列误差有源校正算法

Aiming at the problem of multipath propagation of the calibration source, the multiplicative array error (referring to gain-and-phase error or mutual coupling) calibration algorithms in the presence of multipath propagation are presented. The array is rotated to different locations in order to receive the calibration signal from a far-field and constant waveform source. Based on the received data, the optimization model with respect to array error parameters, multipath propagation azimuths, and complex attenuation coefficients is constructed according to the maximum likelihood (ML) criterion. The concentrated Newton iteration algorithm is derived to solve the optimization model. Furthermore, Cramer-Rao bound (CRB) for unknown parameters is presented. Simulation experiments validate the effectiveness of the proposed algorithms and demonstrate that the asymptotic performance of the novel algorithms can reach the corresponding CRB.

Improved Direction-of-Arrival Estimation for Uncorrelated and Coherent Signals in the Presence of Multipath Propagation

Improved Direction-of-Arrival Estimation for Uncorrelated and Coherent Signals in the Presence of Multipath Propagation

Coherent UWB Ranging in the Presence of Multiuser Interference

Roundtrip time-of-arrival (ToA) measurements employing ultra-wideband (UWB) signals can provide high-precision ranging information. However, the accuracy is degraded by multiuser interference (MUI), in particular in the presence of multipath propagation. While the processing gain of time-hopping impulse radio (TH-IR) can be used to suppress the MUI, this is often insufficient. We propose instead a nonlinear processing scheme of TH-IR that effectively suppresses MUI without requiring knowledge of the time-hopping sequences of the interfering users. The principle is that multipath components (MPCs) of interferers do not align closely, for the majority of transmission frames, with the MPCs of the desired signal. Through a judicious choice of algorithm parameters we show that our algorithm is superior to existing (realizable) thresholding and median filter algorithms, and in some cases can even beat genie-aided thresholding algorithms. The performance is robust to both strength and number of the interferers. The results are validated with both standardized 802.15.4a channel models and measured outdoor UWB channels.

Measurement, Characterization, and Modeling of the Helicopter Satellite Communication Radio Channel

The satellite-to-helicopter radio channel is measured, characterized, analyzed, and modelled. We used a sweep time delay cross correlation sounder operating at 14.25 GHz and actual helicopters for the experiment. From the measurements, signal fading, delay and Doppler spread are estimated. Wideband radio channel results show that the signal delay spread is small enough, so 32 MHz satellite transponders could be used with no need of equalization. We also observed two important propagation impairments on the received signal envelope, both of them caused by the main rotor blades. The first one is the power attenuation produced when the LoS is obstructed by the blades. We demonstrate that this effect could be mitigated by using spatial or polarization diversity technique in the receiver end. The second one is the presence of multipath propagation leading to a power level oscillation dependent on the amplitude of the received multipath components. An UTD-based 3-D ray tracing model was used to conclude that the main multipath components are generated by diffraction on the rotor blade edges.