Indoor Multipath Environment Research Articles

Improving RF-DNA Fingerprinting Performance in an Indoor Multipath Environment Using Semi-Supervised Learning

Improving RF-DNA Fingerprinting Performance in an Indoor Multipath Environment Using Semi-Supervised Learning

Analysis and Design of a MuSiC-Based Angle of Arrival Positioning System

In this research article, a concept for a secondary RAdio Direction And Ranging (RADAR) angle of arrival based system with cooperative targets transmitting at 2.4 GHz and using Multiple Signal Classification (MuSiC) to determine the angles of incidence is investigated. In addition to introducing common algorithms and presenting thorough derivations, the system is first examined through simulations. To prove the concept, hardware, firmware, and software are developed. For MuSiC, we propose three novel methods to obtain the correct incident angle from the spectrum, especially in strong multipath environments. These methods work either for a single spectrum or for a combination recorded at multiple times. Together with the estimated angles of incidence, our methods determine measures on the respective likelihoods. Based on this, we additionally propose two algorithms for computing the final position. Our system is characterized in both a simple 20 m × 15 m outdoor and a 17 m × 13 m multipath indoor environment, where we achieve a mean angular error of 3∘ and a mean positioning error of 0.67 m for the former using only four base stations with four antennas each. Our novel approach shows position accuracy improvements of 15% outdoors and 25% indoors compared to classical MuSiC estimation.

Эффект «волновода» при распространении сверхширокополосных сигналов в помещении

“Waveguide” effect that occurs by indoor propagation of ultrawideband signals is shown. The effect exhibits itself in the absence of interference factor of signal dissipation at any distance. Unlike outdoor propagation, the signal attenuation in multipath indoor environment is similar to free space. The effect occurs due to reflections of the incident wave from paired opposite surfaces, e.g., floor – ceiling, parallel walls. As a result, the distance range of indoor ultrawideband communications is essentially higher than outdoors. The effect is simulated in a three-ray reflection model.

3-D Motion Imaging in a Multipath Coordinate Space Based on a TDM-MIMO Radar Sensor

To date, 3-D radar imaging of moving objects in a multipath coordinate space close to antennas remains a technical challenge. In this work, we demonstrate the implementation of such 3-D motion imaging based on a continuous-wave, multiple-input multiple-output (MIMO) Doppler radar sensor (DRS). Working with a time-division-multiplex (TDM) scheme, this portable, cost-effective DRS is a bistatic system with one transmitting and one receiving channels, and a radio frequency (RF) switch in each channel toggling between two antennas. Assisted by algorithms specifically derived for the TDM-MIMO architecture, highly sensitive 3-D imaging performed in a multipath indoor environment was experimentally implemented. Numerical simulations and experimental demonstrations verified the effectiveness and accuracy of the proposed approach.

A High Accuracy Positioning Method for Single Base Station in Indoor Emergency Environment

Objectives In recent years, the demand of indoor and outdoor emergency location service is growing rapidly. Affected by indoor space environment, signal types, sensor performance and other factors, the existing positioning methods of single signal source, single sensor source, integrated navigation, fusion positioning are not perfect in accuracy, stability, reliability, rapidity and other aspects. The main objective of this study is to propose a high precision wireless location method for single base station in emergency positioning environment. Methods A method of angle measurement with high precision was proposed to eliminate redundant phase caused by modulated signal and sequential sampling. Firstly, a circular antenna array was constructed which sampling received signal on one channel by switching the dual polarized antenna array element in turn, and on the second channel by comparison antenna. Then, the echo signal mathematical model of dual channel antenna was established. Finally, the super-resolution angle estimation algorithm of Capon spectral and polarization decoupling was given for multipath indoor environment. In order to reduce the computational complexity of four-dimensional search, the steering vector was rewritten by hardard product, and target angle estimation was obtained by solving the minimum eigenvalue to minimize the cost function. Results From the comparison results of array phases between single channel and dual channel, it can be seen that the proposed two channel antenna has better phase stability. Experimental results on several fixed location points demonstrate that the root mean square(RMS) positioning error in X direction and Z direction is better than 0.5 m. Both static and dynamic tests show that the influence of source signal phase and frequency synchronization error to switch-antenna array can be effectively eliminated. Conclusions The proposed method can achieve two-dimensional accurate localization with a single base station, which has wider application than the single channel switch-antenna array and is easy to rapid deployment in emergency positioning environment.

Wi-Fi For Indoor Device Free Passive Localization (DfPL): An Overview

The world is moving towards an interconnected and intercommunicable network of animate and inanimate objects with the emergence of Internet of Things (IoT) concept which is expected to have 50 billion connected devices by 2020. The wireless communication enabled devices play a major role in the realization of IoT. In Malaysia, home and business Internet Service Providers (ISP) bundle Wi-Fi modems working in 2.4 GHz Industrial, Scientific and Medical (ISM) radio band with their internet services. This makes Wi-Fi the most eligible protocol to serve as a local as well as internet data link for the IoT devices. Besides serving as a data link, human entity presence and location information in a multipath rich indoor environment can be harvested by monitoring and processing the changes in the Wi-Fi Radio Frequency (RF) signals. This paper comprehensively discusses the initiation and evolution of Wi-Fi based Indoor Device free Passive Localization (DfPL) since the concept was first introduced by Youssef et al. in 2007. Alongside the overview, future directions of DfPL in line with ongoing evolution of Wi-Fi based IoT devices are briefly discussed in this paper.

A New Cycle Slip Detection and Repair Method Using a Single Receiver's Single Station B1 and L1 Frequencies in Ground-Based Positioning Systems.

The detection and repair of the cycle slip is a key step for high precision navigation and positioning in indoor environments. Different methods have been developed to detect and repair cycle slips for carrier phase processing. However, most approaches are designed to eliminate the effects of the ionosphere in an outdoor environment, and many of them use pseudorange (code) information that is no longer suitable for indoor multipath environments. In this paper, a method based on the geometry-free combination without the pseudorange data is proposed to detect and fix cycle slips. A ground-based navigation system is built for data collection. Unlike the traditional dual-frequency cycle slip detection method, the Beidou B1, GPS L1 carrier phase combination is used instead of the B1, B2, or L1, L2 carrier phase combination, Ublox is used for data collecting. For fixing the cycle slips quickly, an improved adaptive Particle Swarm Optimization (PSO) algorithm is employed. We compared the performance of the new method with the existing two methods using simulated data in different conditions. The results show that the proposed method has better performance than other methods.

Investigation of Time-Reversal Based Far-Field Wireless Power Transfer From Antenna Array in a Complex Environment

The performance of time-reversal (TR) based far-field wireless power transfer (WPT) from an antenna array in a complex propagation environment is investigated in comparison with conventional array-based beamforming (BF). A two-step experiment is performed, namely 1) the propagation stage and 2) rectification stage. In the propagation stage, signal transmission is measured between the transmit array and receive antenna in an indoor multipath environment, for line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. The results demonstrate that TR results in higher peak voltage compared to BF given the same average transmit power. In addition, while BF loses its ability to selectively send waves at the receiver due to impairment of the beam from multipath, TR can selectively focus waves at the receiver by inherently taking advantage of multipath. In the rectification stage, the resulting signals from the propagation stage are fed into a broadband rectifier for RF-to-DC conversion. It is shown that the signals received using TR lead to higher rectified DC voltage and rectification efficiency. The overall results suggest that TR can outperform BF with higher rectification efficiency given the same average transmit power. Through optimization of the TR pulse interval, array configuration and transmit power, further improvement in the performance of TR based WPT in a complex propagation environment is possible.

Noise Adaptive Optimization Scheme for Robust Radio Tomographic Imaging Based on Sparse Bayesian Learning

This paper addresses the robust signal reconstruction problem caused by different types of noise in radio tomographic imaging (RTI). Most of the existing reconstruction algorithms are built on the assumption of Gaussian noise, which is not the case for practical RTI systems, especially in indoor multipath environments. To weaken the effect of different types of noise on RTI performance, we propose a noise adaptive optimization scheme with sparse Bayesian learning (SBL). Specifically, we model the noise as a mixture of Gaussians (MoG) distribution, which provides the flexibility for describing the unknown and time-varying RTI noise. We further automatically estimate the MoG model parameters as well as the signal under a SBL framework, which makes the signal reconstruction more robust to the complex noise and even outliers. Experimental results in the context of device-free localization show that the proposed scheme can effectively reduce mislocalization and improve localization accuracy in the rich multipath environments, as compared with state-of-the-art reconstruction methods.

A time-of-arrival estimation algorithm for OFDM signals in indoor multipath environments

Time-of-arrival (TOA) estimation of OFDM signals in multipath channels is challenging, especially when the signal bandwidth is limited, such as is the case of WIFI. In this paper, a novel low complexity TOA estimation algorithm is developed for OFDM signals that is robust to various multipath environments. We approximate the received signal as Gaussian with an autocorrelation that can be predetermined by the environment characteristics, and then derive the Maximum Likelihood estimator with an efficient implementation algorithm. The estimator performance was tested with a measurement system that was developed based on off-the-shelf WIFI 802.11g routers. The measurement system enabled the evaluation of the estimator performance in real-life indoor environments, and with real-life OFDM transmitter and receiver imperfections. The results show that the novel TOA estimator outperforms other known reference methods over various indoor environments.

BreathTrack: Tracking Indoor Human Breath Status via Commodity WiFi

In this paper, we propose a contact-free breath tracking system, BreathTrack, to track the status of breath using the off-the-shelf WiFi devices. BreathTrack exploits the phase variation of the channel state information (CSI) to track human breath. To resolve the phase distortions introduced by the hardware imperfection of the commodity WiFi chips, BreathTrack utilizes both the hardware and software correction methods. The time-invariant PLL phase offset is calibrated by the hardware correction using cables and splitters, while the time-varying carrier frequency offset, sampling frequency offset and packet detection delay are removed by the software corrections using the phase difference between the CSI at the receiver antennas and that at the reference antenna connected from the transmitter. Moreover, BreathTrack utilizes the sparse recovery method to find the dominant path in the multipath indoor environment and derive the corresponding complex attenuation coefficient. Then, the phase variation of the complex attenuation coefficient is utilized to extract the detailed breath status and the breath rate. Extensive experiments are conducted to show that BreathTrack could estimate the breath rate with the median accuracy of over 99% in most scenarios, and could track the detailed status of breath directly using the raw phase variation.

A new method for path-loss modeling

AbstractIn this paper, a new path-loss model for electromagnetic wave in an indoor multipath environment is proposed based on matching coefficient, polarization matching factor, and normalized field intensity direction function. This model is called the Friis-extension (Friis-EXT) model, because it operates as the Friis model under certain conditions. In addition, in the modeling process of the path-loss in an indoor environment, the reflective surfaces in the environment and form of the antenna are considered. Afterwards, the path-loss data in an indoor corridor environment are measured, and the maximum error between the theoretical value and the measured data is <7.5 dB. Finally, the Friis-EXT model is compared with some other traditional models, and the results show that the Friis-EXT model is the best one that matches the measurement data.

TOA Estimation of Chirp Signal in Dense Multipath Environment for Low-Cost Acoustic Ranging

In this paper, a novel time of arrival (TOA) estimation method is proposed based on an iterative cleaning process to extract the first path signal. The purpose is to address the challenge in dense multipath indoor environments that the power of the first path component is normally smaller than other multipath components, where the traditional match filtering (MF)-based TOA estimator causes huge errors. Along with parameter estimation, the proposed process is trying to detect and extract the first path component by eliminating the strongest multipath component using a band-elimination filter in fractional Fourier domain at each iterative procedure. To further improve the stability, a slack threshold and a strict threshold are introduced. Six simple and easily calculated termination criteria are proposed to monitor the iterative process. When the iterative “cleaning” process is done, the outputs include the enhanced first path component and its estimated parameters. Based on these outputs, an optimal reference signal for the MF estimator can be constructed, and a more accurate TOA estimation can be conveniently obtained. The results from numerical simulations and experimental investigations verified that, for acoustic chirp signal TOA estimation, the accuracy of the proposed method is superior to those obtained by the conventional MF estimators.

Phased-Based Composite Ranging for Backscatter RF Tags: System Analysis and Measurements

A phase-based composite ranging system is investigated that provides accurate and absolute distance estimates for backscatter radio frequency (RF) tags by combining the range estimates of a dual-frequency, continuous-wave (DFCW) and a continuous-wave (CW) radar. The relatively low-resolution DFCW range estimate is used to resolve the wavelength ambiguity in the CW radar, and the disambiguated CW range estimate provides the final, high-resolution, accurate range estimate. Two data fusion methods for combining the DFCW and CW range estimates are proposed and their performance is compared based on measurement results with a backscatter RF tag system operating in the 5.8 GHz industrial, scientific, and medical (ISM) frequency band. Each data fusion method uses spatial averaging, as the RF tag is moved through space to reduce the overall system error. The efficacy of spatial averaging is investigated by showing that multipath and hardware imperfections cause oscillating errors in the phase used for ranging and the errors are significantly reduced through spatial averaging. It is shown that the proposed system can achieve millimeter-level ranging resolution in a typical indoor multipath environment while adhering to the bandwidth constraints of the 5.8 GHz ISM frequency band.

DoA Estimation Using Compact CRLH Leaky-Wave Antennas: Novel Algorithms and Measured Performance

Traditional direction-of-arrival (DoA) estimation algorithms for multielement antenna arrays (AAs) are not directly applicable to reconfigurable antennas due to inherent design and operating differences between AAs and reconfigurable antennas. In this paper, we propose novel modifications to the existing DoA algorithms and show how these can be adapted for real-time DoA estimation using two-port composite right/ left-handed (CRLH) reconfigurable leaky-wave antennas (LWAs). First, we propose a single/two-port multiple signal classification (MUSIC) algorithm and derive the corresponding steering vector for reconfigurable LWAs. We also present a power pattern cross correlation algorithm that is based on finding the maximum correlation between the measured radiation patterns and the received powers. For all algorithms, we show how to simultaneously use both ports of the two-port LWA in order to improve the DoA estimation accuracy and, at the same time, reduce the scanning time for the arriving signals. Moreover, we formulate the Cramer–Rao bound for MUSIC-based DoA estimation with LWAs and present an extensive performance evaluation of MUSIC algorithm based on numerical simulations. In addition, these results are compared to DoA estimation with conventional AAs. Finally, we experimentally evaluate the performance of the proposed algorithms in an indoor multipath wireless environment with both line-of-sight (LoS) and non-LoS components. Our results demonstrate that DoA estimation of the received signal can be successfully performed using the two-port CRLH-LWA, even in the presence of severe multipath.

Compact Inband Full-Duplex Relays With Beyond 100 dB Self-Interference Suppression: Enabling Techniques and Field Measurements

In this communication, the self-interference (SI) channel and the novel enabling techniques for a compact inband full-duplex relay are described and characterized in different operating environments. The full-duplex operation is based on a novel antenna design that uses wavetraps to provide passive isolation of up to 70 dB between the transmit and receive antenna ports. The passive isolation is complemented with novel active RF and digital cancellation stages that further suppress the residual SI to the receiver noise floor. Measurement results of a complete prototype implementation show that the proposed design can achieve an overall SI cancellation performance of over 100 dB even with an ambitious instantaneous bandwidth of 80 MHz. Similar results are obtained both in an anechoic chamber as well as in realistic multipath indoor environments.

Real‐world testbed for multi‐tag UWB chipless RFID system based on a novel collision avoidance MAC protocol

ABSTRACTChipless radio frequency identification (RFID) tags are dummy, memoryless, with limited number of bits, very low backscattered power, and short reading range. Therefore, the existing RFID standards and protocols designed for the chipped RFID systems are not applicable for the chipless systems. Main objective of this contribution is to introduce a novel real‐world testbed for multi‐tag ultra‐wideband (UWB) chipless RFID system. In this testbed, a new Notch Position Modulation scheme is implemented as the first medium access control algorithm for handling the multi‐tag identification scenario of the frequency signature based chipless RFID tags. This intelligent Notch Position Modulation algorithm reduces the sensing and identification time and accordingly the overall system latency. The proposed protocol enables fetching the frequency signatures of the chipless RFID tags through the whole UWB range effectively. Moreover, an advanced signaling scheme is designed for the RFID reader in order to make the best use of the Federal Communications Commission UWB regulations for increasing the maximum transmitted power and the corresponding reading range. The signaling scheme, real‐time channel estimation, and clutter removal technique are implemented on the software defined radio platform in a heavily dense multipath indoor environment. Based on the medium access control protocol, the mitigation of the undesired environmental reflections as well as the interference between the chipless RFID tags is well demonstrated in the developed testbed.

An efficient higher-order PML in WLP-FDTD method for time reversed wave simulation

Derived from a stretched coordinate formulation, a higher-order complex frequency shifted (CFS) perfectly matched layer (PML) is proposed for the unconditionally stable finite-difference time-domain (FDTD) method based on weighted Laguerre polynomials (WLPs). The higher-order PML is implemented with an auxiliary differential equation (ADE) approach. In order to further improve absorbing performance, the parameter values of stretching functions in the higher-order PML are optimized by the multi-objective genetic algorithm (MOGA). The optimal solutions can be chosen from the Pareto front for trading-off between two independent objectives. It is shown in a numerical test that the higher-order PML is efficient in terms of attenuating propagating waves and reducing late time reflections. Moreover, the higher-order PML can be placed very close to the wall when analyzing the channel characteristics of time reversal (TR) waves in a multipath indoor environment. Numerical examples of TR wave propagation demonstrate the availability of the proposed method.

Indoor Localization Using 802.11 Time Differences of Arrival

This paper proposes a novel time-based method for determining the position of an IEEE 802.11g transmitter using multiple mutually synchronized 802.11g receivers. By means of baseband signal processing, the proposed algorithm obtains a high-resolution estimate of the time of arrival (TOA) of the long training sequence symbol at each receiver. An estimate of the position of the transmitter is obtained based on the estimation of the time differences of arrival (TDOA) of the symbols and the known fixed locations of the receivers. This paper investigates the effects of carrier and sampling clock offsets, in both frequency and phase, between nodes on the TOA and TDOA estimation error. In real-world experiments in a line of sight, low multipath indoor environment, the method was found to achieve mean errors of 42 cm per symbol for 1-D and 1.39 m per symbol for 2-D position estimation, for ranges of up to 25 m.

Compressive Sensing-Based Multipath Exploitation for Stationary and Moving Indoor Target Localization

Compressive sensing (CS)-based multipath exploitation has been successfully applied to stationary indoor scenes in through-the-wall radar imaging (TWRI). The benefits of using significantly reduced data are also desirable for moving targets. Hence, we bring CS based multipath exploitation to the non-stationary target domain and are able to treat moving and stationary targets simultaneously. In general, multipath propagation has adverse effects on the image quality. However, by using proper modeling, multipath can be used to one’s advantage. In this paper, we apply CS to both stationary and moving targets under interior wall scatterings. Assuming knowledge of the room geometry, we develop an effective method that solves the inverse problem of joint localization and velocity estimation of the targets in an indoor multipath environment from a few measurements. We also propose a computationally inexpensive scheme that first locates the targets using sparse reconstruction and subsequently estimates the velocity vectors. Effectiveness of the proposed methods is demonstrated using both simulated and experimental data.