Impulsive acoustic source localization via wireless sensor Imote2

Radar sensors are an attractive technology for different kinds of applications, especially, in the case of safety driving systems. This research deals with designing the target return signal detection algorithm for radar sensors using the generalized detector (GD) with adaptive detection threshold based on a sliding window technique to estimate the noise power. The general GD structure is introduced, and the proposed method to define the adaptive detection threshold is assumed to be employed by 24 GHz frequency modulation continuous wave (FMCW) radar sensor and the simulation results show the better detection performance in comparison with the cell averaging constant false alarm rate (CA-CFAR) detector one which is widely used by radar sensor systems for car applications.

Since fiber distributed vibration sensing (DVS) system based on phase-sensitive optical time domain reflectometer (Φ-OTDR) is extremely sensitive to the ambient environment, how to improve signal-to-noise ratio (SNR) and obtain vibration signal from background noise has become a key problem in the field. In this paper, firstly, based on the analysis of the wavelet high frequency component location algorithm and the separating averaging and differential algorithm, an improved separating averaging and differential algorithm is proposed by introducing an interval. Then cell average constant false alarm rate (CA-CFAR) detection algorithm is used to set the adaptive threshold. Finally, the continuous vibration section is found according to the influenced-spatial scale of the pipeline intrusion vibration, and the middle position of the section is judged to be the vibration position. The experimental results show that the positioning algorithm has less positioning error, shorter runtime and higher SNR. The SNR can be as high as 9.3483dB and the computation amount of the next identification module is reduced.

Recently, indoor positioning has been one of the hot topics in the field of navigation and positioning. Among different solutions on indoor positioning, positioning with acoustic signals has its promise due to its relatively high accuracy in the line of sight scenarios, low cost, and ease of being implemented in smartphones. In this work, a novel acoustic positioning method, called RATBILS, is proposed, in which encoded chirp acoustic signals are modulated and transmitted by different acoustic base stations. The smartphones receive the signals and perform the following three steps: (1) preprocessing; (2) time of arrival (TOA) estimation; and (3) time difference of arrival (TDOA) calculation and location estimation. In the preprocessing stage, we use band pass filters to filter out low-frequency noise from the environment. At the same time, we perform a signal decoding function in order to lock onto the positioning source. In the TOA estimation stage, we conduct both coarse and fine detection to enhance the accuracy and robustness of TOA estimation. The primary goal of coarse detection is to establish a noise range for fine detection. The main objective of fine detection is to emphasize the intensity of the first arrival diameter and resistance with multipath and non-line-of-sight (NLOS) caused by human body obstruction. In the TDOA calculation and location estimation stage, we estimate the TDOA based on the TOA estimation and then use the TDOA results for position estimation. In order to evaluate the performance of the proposed RATBILS system, two indoor field tests are carried out. The test results show that the RATBILS system achieves a positioning error of 0.23 m at 92% in region 1 of scene 1 and is superior to the traditional threshold method. The RATBILS system achieves a positioning error of 0.56 m at 92% in region 2 of scene 1 and is superior to the traditional threshold method. In scene 2, the maximum average positioning error was 1.26 m, which is better than the 3.33 m and 3.87 m of the two traditional threshold methods.

Accurate localization has gained significant interest in the field of sensor networks, impulse radio60GHz signals which is low cost, low complexity are even much more practical for ranging, localization and tracking systems because of the high time and multipath resolution and so on. Typically, accurate Time of Arrival (TOA) estimation of the 60GHz signals is very important. In order to improve the precision of the TOA estimation, a new TOA estimation algorithm based on Energy Detector is proposed which is based on a joint metric of the Skewness, Kurtosis, Maximum Slope and Standard Deviation after Energy Detection. The best threshold based on the signal-to-noise ratio (SNR) is investigated and the effects of the integration period and channel model are examined. Simulation results are presented which show that for theIEEE802.15.3c channel models CM1.1 and CM2.1, the proposed algorithm provides better precision and robustness in both high and low SNR environments than other ED-based algorithms.

Range estimation is the core of many positioning systems such as radar, and Wireless Local Positioning Systems (WLPS). The estimation of range is achieved by estimating Time-of-Arrival (TOA). TOA represents the signal propagation delay between a transmitter and a receiver. Thus, error in TOA estimation causes degradation in range estimation performance. In wireless environments, noise, multipath, and limited bandwidth reduce TOA estimation performance. TOA estimation algorithms that are designed for wireless environments aim to improve the TOA estimation performance by mitigating the effect of closely spaced paths in practical (positive) signal-to-noise ratio (SNR) regions. Limited bandwidth avoids the discrimination of closely spaced paths. This reduces TOA estimation performance. TOA estimation methods are evaluated as a function of SNR, bandwidth, and the number of reflections in multipath wireless environments, as well as their complexity. In this research, a TOA estimation technique based on Blind signal Separation (BSS) is proposed. This frequency domain method estimates TOA in wireless multipath environments for a given signal bandwidth. The structure of the proposed technique is presented and its complexity and performance are theoretically evaluated. It is depicted that the proposed method is not sensitive to SNR, number of reflections, and bandwidth. In general, as bandwidth increases, TOA estimation performance improves. However, spectrum is the most valuable resource in wireless systems and usually a large portion of spectrum to support high performance TOA estimation is not available. In addition, the radio frequency (RF) components of wideband systems suffer from high cost and complexity. Thus, a novel, multiband positioning structure is proposed. The proposed technique uses the available (non-contiguous) bands to support high performance TOA estimation. This system incorporates the capabilities of cognitive radio (CR) systems to sense the available spectrum (also called white spaces) and to incorporate white spaces for high-performance localization. First, contiguous bands that are divided into several non-equal, narrow sub-bands that possess the same SNR are concatenated to attain an accuracy corresponding to the equivalent full band. Two radio architectures are proposed and investigated: the signal is transmitted over available spectrum either simultaneously (parallel concatenation) or sequentially (serial concatenation). Low complexity radio designs that handle the concatenation process sequentially and in parallel are introduced. Different TOA estimation algorithms that are applicable to multiband scenarios are studied and their performance is theoretically evaluated and compared to simulations. Next, the results are extended to non-contiguous, non-equal sub-bands with the same SNR. These are more realistic

Radar usually employs several signal processing methods successively for detection. Each processing step influences the radar detection performance. Thus, analysis of the radar detection performance considering the complete signal processing flow provides significant reference for radar detector design. In this paper, with the assumption that matched filtering, square-law detection, non-coherent integration, cell averaging constant false alarm rate detection and double-threshold detection are employed sequentially for radar detection, radar detection performance in K distributed sea clutter plus Rayleigh distributed thermal noise is analyzed. Mathematical expressions of radar false alarm probability and detection probability are derived. Radar detection performances for four types of Swerling fluctuating targets in various circumstances are presented by simulation. And comprehensive effect of K distributed sea clutter plus Rayleigh distributed thermal noise on radar detection performance is analyzed.

In an ultra-wideband (UWB) system, the two-dimensional (2D) multiple signal classification (MUSIC) algorithms based on high-precision 2D spectral peak search can jointly estimate the time of arrival (TOA) and angle of arrival (AOA). However, the computational complexity of 2D-MUSIC is very high, and the corresponding data model is only based on the dual antennas. To solve these problems, a low-complexity algorithm for joint AOA and TOA estimation of the multipath ultra-wideband signal is proposed. Firstly, the dual antenna sensing data model is extended to the antenna array case. Then, based on the array-sensing data model, the proposed algorithm transforms the 2D spectral peak search of 2D-MUSIC into a secondary optimization problem to extract the estimation of AOA via only 1D search. Finally, the acquired AOA estimations are brought back, and the TOA estimations are also obtained through a 1D search. Moreover, in the case of an unknown transmitted signal waveform, the proposed method can still distinguish the main path signal based on the time difference of arrival of different paths, which shows wider applications. The simulation results show that the proposed algorithm outperforms the Root-MUSIC algorithm and the estimation of signal parameters using the rotational invariance techniques (ESPRIT) algorithm, and keeps the same estimation accuracy but with greatly reduced computational complexity compared to the 2D-MUSIC algorithm.

In this thesis, we cope with the fundamental mathematical and physical problems of the space-time-Doppler UWB system design for fading channels: multi-input multi-output (MIMO) wireless communication with adaptive filtering. The estimation algorithm from equalizer providing an accurate parameters estimate is investigated. UWB radio is a fast emerging technology with uniquely attractively features inviting major advances in wireless communications, networking, radar, imaging, and positioning systems. By its rule-making proposal in 2002, the Federal Communications Commission (FCC) in the United States essentially unleashed huge new bandwidth (3.6-10.6 GHz) at the noise floor, where UWB radios overlaying coexistence RF systems cerate using low-power ultra-short information bearing pulses. Right now, there are three basic types of UWB: multiband OFDM UWB (MB-OFDM UWB), impulse-UWB (I-UWB), and direct sequence UWB (DS-UWB). We focus on I-UWB and MB-OFDM-UWB, and compare their performance. A simple means for spreading the spectrum of low duty cycle pulse trains is time hopping (TH), with pulse position modulation (PPM) for data modulation at the rate of many pulses per data bit. The main contribution of this thesis for I-UWB is the design of leading edge detectors, coherent correlation detector (CCD), and pilot performance enhancement compared with different Rayleigh and Ricean fading conditions. For MB-OFDM UWB, we have considered the performance analysis and design criteria of MIMO OFDM UWB systems for high data-rate wireless transmission. The signal processing of frame detection, time synchronization, frequency synchronization, channel estimation, synchronization tracking using pilot subcarriers and 2-D MIMO detection algorithms is discussed. The main contributions of this thesis are 1) Compared with receiver employing the Maximum Likelihood (ML) detector, the receiver employing a low-complexity linear Minimum Mean Square Error (MMSE) demodulator can perform a limited performance loss in spatially uncorrelated channels. 2) Due to the operations of spreading and dispreading combined with MMSE-based frequency domain equalization, the adverse effects of the low-SNR subcarriers on the average BER performance are potentially improved. This is a direct consequence of spreading, because even if the signal corresponding to a specific chip is obliterated by a deep frequency domain channel fade, after dispreading these effects are spread over the Walsh-Hadamard Transform (WHT) length. Hence there is a high chance of still recovering all the partially affected subcarrier symbols without errors. 3) As a test case, the OFDM-based 200 Mb/s MB-UWB network (IEEE 802.15.3a) are considered, but the simulation results are shown above section. 4) The simulation channel can be easily applied to NOS and NLOS situation with WHT transformation from Simulink model. The fading channels of UWB with low/high signal to noise ratio (SNR), multipath effects, and multiuser interference may introduce large errors in location. The location engine performs the following tasks: █ Data fusion techniques: Different data fusion techniques are implemented using Time Of Arrival (TOA), Angle Of Arrival (AOA), or a combination of both. █ Channel modeling: A multipath, multiuser channel environment is created that models path loss, shadowing, Rayleigh fading, and Doppler frequency effects. █ Parameter estimation: TOA and AOA estimation algorithms are implemented as part of the location finding engine. Different variations of algorithms are implemented for performance and comparison purposes. █ Configuring the physical layer for different wireless networks. Among the programmable parameters are spreading factor, packet size, training length, constellation type, modulation technique, carrier frequency, level of transmitted signal power, and the number of antennas at the transmitter for both sides. █ Configuring the mobile user conditions. The wireless channel models depend on the Doppler frequencies present in the environment. The Doppler frequency depends on the mobile speed and carrier frequencies as input and generates a Rayleigh fading channel with the U-shape Doppler spectrum. █ Configuring the environmental parameters and network geographical structure. One of the factors affecting the performance of the wireless location system is the environment type (e.g., bad urban, urban, suburban, or rural area). For example, in a bad urban area with many blocking objects and buildings, non-line of sight (NLOS) effects plays an important role in the estimation accuracy.

This paper analyses the performances of a Direction of Arrival (DoA) localization algorithm based on the use of phaseless magnitude data coming from a Time of Arrival (ToA) estimation. The localization system architecture key component consists of a broadband switched beams antenna (SBA) connected to a corresponding broadband radio front-end. The receiver collects sample data being synchronized with the antenna beam, while both ToA and DoA estimations rely only on scalar data. Differently from the available literature, the proposed system doesn't locate the DoA by implementing the Time Difference of Arrival (TDoA) paradigm, but instead this is made possible by using the phaseless data of the impinging signal power, exploiting the signal magnitude gradient between SBA elements, a byproduct of the ToA estimation. Experimental results demonstrate how different algorithms lead to an angular precision with a mean error inferior to 3°.

The Time Difference of Arrival (TDOA) of an acoustic source with respect to a given pair of microphones is typically estimated as the maximizer of a Measure of Synchrony (MoS) between the pair of microphone signals, within the interval [−D/v, D/v], where D is the inter-microphone distance and v is the speed of sound. In practical enclosures, phantom sources are created due to reverberation, which can cause false peaks in the MoS, leading to erroneous TDOA estimates. In several practical enclosures such as meeting rooms, conference halls, lecture halls, etc., the regions which can admit an acoustic source are restricted, because of furniture and other fixtures. Consequently, it is possible to acquire prior knowledge of the region which can accommodate an acoustic source. In this paper, we propose an approach to utilize this prior knowledge of source region for accurate TDOA estimation. We transform the prior knowledge of source region into an interval of possible TDOAs using a newly developed concept of family of hyperboloids. This interval, referred to as Region Constrained TDOA Interval (RCTI) is shown to be smaller than [−D/v, D/v]. TDOA is then estimated as the maximizer of a suitable MoS within the RCTI. We demonstrate that estimating TDOA within RCTI, with generalized cross correlation (GCC) class of functions as MoS, is more robust to reverberation than estimating TDOA within [−D/v, D/v].

Data acquisition and Signal Processing is an important part of frequency modulated continuous wave (FMCW) radar system. In recent year P2ET-LIPI was developing FMCW navigation radar system in portable size. The main component of data acquisition for navigation radar is highspeed Analog to Digital Conversion (ADC) USB-2020 board and signal processing algorithm has been developed using Visual C# 2015 Community Edition. USB-2020 board has two channel ADC on board with 12 bits resolution and operated in a burst-io mode to get maximum sampling rate at 20 MS/s. A timing generator for synchronization between ADC and linear frequency modulation (LFM) chirp generator is developed using Complex Programmable Logic Device (CPLD) Max II series based on VHSIC hardware description language (VHDL). Signal processing unit consists of windowing function to reduce side- lobe suppression, Fast Fourier Transform (FFT) function to get range information and adaptive threshold using three algorithms of Constant False Alarm Rate (CFAR): Cell Averaging (CA), Order Statistic (OS) and Variable Index (VI) CFAR. The experiment shows that the data acquisition module can capture In-phase and Quadrature (I/Q) beat signal and signal processing algorithm can detect object/target from the noise.

In this paper, we propose a parallel processing architecture, based on two TMS320C44 VME-bus DSP boards, for real time implementation of Cell Averaging and Clutter Map Constant False Alarm Rate (CFAR) detectors, and a data extractor based on a centroidal interpolation of the position of the detected target. The optimal processing speed has been achieved by fully exploiting the capacities of the dasiaC44 processor. The implemented system is well adapted for two dimension radars. The overall processing scheme interconnections and the real time implementation results are presented and discussed.

Due to the significance of positioning in complicated electromagnetic environment of its variety of applications, wireless localization techniques have attracted significant research interests with the trends moving toward boosting the capabilities of multi-objective cooperative networks. This paper addresses the problem of locating multiple targets in 3-D cooperative wireless sensor network. A novel hybrid received signal strength (RSS) and time-of-arrival (TOA) positioning scheme is proposed. Employing RSS and TOA measurements, four valuable expressions are drawn. The TOA and RSS technologies are combined with path loss difference variable being introduced. Based on the weighted least squares criterion, the rough solutions of multiple targets positions are derived. Finally, the locations of obtained targets are optimized by cooperative wireless communication between the target and another target. The location accuracy of the proposed estimation algorithm is analyzed and compared with the conventional RSS and TOA estimation algorithms through simulation experiments. The simulation result demonstrates that the proposed hybrid RSS and TOA localization algorithm for multi-objective cooperative wireless networks outperforms traditional approaches.

Digital television signal is a promising signal of opportunity for wireless positioning. This paper studies the time of arrival (TOA) estimation on the European standard DVB-T signals in the context of positioning. Theoretical analysis on the autocorrelation of the pilot signal and multipath error envelop suggests that DVB-T has the appropriate characteristics for positioning. A software defined radio-based DVB-T receiver is developed for field testing, in which the radio frequency DVB-T signals are first sampled by universal software radio peripheral, and then algorithms of the coarse symbol synchronization, the pilot detection, the first path acquisition, and the delay tracking are sequentially performed to obtain the TOA estimation. To quantify the TOA tracking results on real DVB-T signals, field testing campaigns are carried out in five cities in Southern France. Test results showed that, in the high signal-noise ratio condition, the 2- $\sigma$ error interval is within 1 m. By taking into account all the field tests, the interval of 95% accuracy is within 4 m and the corresponding ${C/N_{0}}$ varies from 48 to 62 dB-Hz. In addition, with the developed TOA estimation method, the synchronization of the emitters with global positioning system time is evaluated and the distance difference of the multiple emitters within single frequency networks are also measured during the tests.

Publication in the conference proceedings of EUSIPCO, Poznan, Poland, 2007