Model-based asymptotically optimal dispersion measure correction for pulsar timing

In order to reach the sensitivity required to detect gravitational waves, pulsar timing array experiments need to mitigate as much noise as possible in timing data. A dominant amount of noise is likely due to variations in the dispersion measure. To correct for such variations, we develop a statistical method inspired by the maximum likelihood estimator and optimal filtering. Our method consists of two major steps. First, the spectral index and amplitude of dispersion measure variations are measured via a time-domain spectral analysis. Second, the linear optimal filter is constructed based on the model parameters found in the first step, and is used to extract the dispersion measure variation waveforms. Compared to current existing methods, this method has better time resolution for the study of short timescale dispersion variations, and generally produces smaller errors in waveform estimations. This method can process irregularly sampled data without any interpolation because of its time-domain nature. Furthermore, it offers the possibility to interpolate or extrapolate the waveform estimation to regions where no data is available. Examples using simulated data sets are included for demonstration.Comment: 15 pages, 15 figures, submitted 15th Sept. 2013, accepted 2nd April 2014 by MNRAS. MNRAS, 201

HIGH RESOLUTION TIME-OF-ARRIVAL RANGING OF WIRELESS SENSOR NODES IN NON-HOMOGENOUS ENVIRONMENTS

Wireless Sensor Networks (WSN) have emerging applications in homogeneous environments such as free space. In addition, WSNs are finding new applications in non-homogeneous (NH) media. All referred applications entail location information of measured data or observed event. Localization in WSNs is considered as the leading remedy, which refers to the procedure of obtaining the sensor nodes relative location utilizing range measurements. Localization via Time-of-Arrival (ToA) estimation has received considerable attention because of high precision and low complexity implementation, however, the traditional techniques are not feasible in NH media due to frequency dispersion of transmitted ranging waveform. In this work, a novel and effective ToA-based ranging technique for localization in NH media consisting of frequency dispersive sub-media is proposed. First challenges of ToA estimation in NH media regarding frequency dispersion is investigated. Here, a novel technique which improves ToA estimation resolution at fixed bandwidth via maximum rising level detector (MRLD) technique is discussed. The MRLD receiver utilizes oversampling and multiple correlation paths to evaluate with high resolution the path corresponding to the maximum rising level of matched filters output. In order to achieve higher resolution, a novel and effective ToA estimation is introduced that incorporates orthogonal frequency division multiple access (OFDMA) subcarriers. In the proposed technique, pre-allocated orthogonal subcarriers are utilized to construct a ranging waveform which enables high performance ToA estimation in dispersive NH media in frequency domain. Here, we show that each frequency component of propagated waveform is received with different time delay and phase which dramatically increases the number of unknowns in the received signal system model. Then, we propose a novel idea based on frequency domain analysis of the transmitted OFDMA subcarriers to reduce the number of unknowns exploiting feasible approximations. Finally, the proposed ToA technique is applied multiple times at different carrier frequencies to create a system of linear equations which can be solved to compute the available sub-mediums thickness and range. Simulation results prove that the proposed technique offers high resolution range measurements given simulated ToA estimation error at different signal to noise ratio regimes in NH media

Power Optimization for Network Localization

Reliable and accurate localization of mobile objects is essential for many applications in wireless networks. In range-based localization, the position of the object can be inferred using the distance measurements from wireless signals exchanged with active objects or reflected by passive ones. Power allocation for ranging signals is important since it affects not only network lifetime and throughput but also localization accuracy. In this paper, we establish a unifying optimization framework for power allocation in both active and passive localization networks. In particular, we first determine the functional properties of the localization accuracy metric, which enable us to transform the power allocation problems into second-order cone programs (SOCPs). We then propose the robust counterparts of the problems in the presence of parameter uncertainty and develop asymptotically optimal and efficient near-optimal SOCP-based algorithms. Our simulation results validate the efficiency and robustness of the proposed algorithms.Comment: 15 pages, 7 figure

Performance Limits and Geometric Properties of Array Localization

Location-aware networks are of great importance and interest in both civil and military applications. This paper determines the localization accuracy of an agent, which is equipped with an antenna array and localizes itself using wireless measurements with anchor nodes, in a far-field environment. In view of the Cram\'er-Rao bound, we first derive the localization information for static scenarios and demonstrate that such information is a weighed sum of Fisher information matrices from each anchor-antenna measurement pair. Each matrix can be further decomposed into two parts: a distance part with intensity proportional to the squared baseband effective bandwidth of the transmitted signal and a direction part with intensity associated with the normalized anchor-antenna visual angle. Moreover, in dynamic scenarios, we show that the Doppler shift contributes additional direction information, with intensity determined by the agent velocity and the root mean squared time duration of the transmitted signal. In addition, two measures are proposed to evaluate the localization performance of wireless networks with different anchor-agent and array-antenna geometries, and both formulae and simulations are provided for typical anchor deployments and antenna arrays.Comment: to appear in IEEE Transactions on Information Theor

A Survey on Fundamental Limits of Integrated Sensing and Communication

The integrated sensing and communication (ISAC), in which the sensing and communication share the same frequency band and hardware, has emerged as a key technology in future wireless systems due to two main reasons. First, many important application scenarios in fifth generation (5G) and beyond, such as autonomous vehicles, Wi-Fi sensing and extended reality, requires both high-performance sensing and wireless communications. Second, with millimeter wave and massive multiple-input multiple-output (MIMO) technologies widely employed in 5G and beyond, the future communication signals tend to have high-resolution in both time and angular domain, opening up the possibility for ISAC. As such, ISAC has attracted tremendous research interest and attentions in both academia and industry. Early works on ISAC have been focused on the design, analysis and optimization of practical ISAC technologies for various ISAC systems. While this line of works are necessary, it is equally important to study the fundamental limits of ISAC in order to understand the gap between the current state-of-the-art technologies and the performance limits, and provide useful insights and guidance for the development of better ISAC technologies that can approach the performance limits. In this paper, we aim to provide a comprehensive survey for the current research progress on the fundamental limits of ISAC. Particularly, we first propose a systematic classification method for both traditional radio sensing (such as radar sensing and wireless localization) and ISAC so that they can be naturally incorporated into a unified framework. Then we summarize the major performance metrics and bounds used in sensing, communications and ISAC, respectively. After that, we present the current research progresses on fundamental limits of each class of the traditional sensing and ISAC systems. Finally, the open problems and future research directions are discussed

Modern Digital Chirp Receiver: Theory, Design and System Integration

Chirp signals can achieve a high range resolution without sacrificing SNR or maximum range, making them a strong candidate for use in radar and sonar applications. Chirp signals are also power efficient and resistant to interference, making them well suited for communication applications as well. The proposed digital high chirp rate receivers will showcase the use of digital instantaneous frequency measurement (IFM) devices for high chirp rate measurement. The receivers are paired with a high resolution time-of-arrival algorithm, capable of detecting the TOA and TOD of a pulse with an average error of less than 2ns. The high resolution pulse detector is vital for the measurement of high chirp rate, short pulse duration chirp signals when no a priori knowledge of the signals or operating environment is available. Three different receivers were designed and implemented in order to target three different applications: linear chirp signals, nonlinear chirp signals, and linear chirp signals with varying pulse widths. In addition to the digital IFM and TOA algorithm, a high rate 43-tap Hilbert Transform was implemented via an FIR filter in order to convert incoming real data from the ADC into its complex signal representation. All three designs were synthesized and successfully tested on a Xilinx Virtex 6 SX475 FPGA which is paired with a Calypso 12-bit ADC sampling at 2.56GHz. All three receivers run at a rate of 320MHz and can measure chirp rates up to 1180MHz in 400ns. The designs boast an overall detection rate of greater than 97% with a false alarm rate of 10^-7 and achieve a frequency measurement error of less than 1% for both chirp rates and carrier frequencies. The receivers can successfully detect and measure chirp signals and stationary carrier frequencies with SNRs 5dB and higher. The largest design, the digital nonlinear chirp receiver only utilizes 13% of the Virtex 6 SX475 FPGA board

Positioning of High-speed Trains using 5G New Radio Synchronization Signals

We study positioning of high-speed trains in 5G new radio (NR) networks by utilizing specific NR synchronization signals. The studies are based on simulations with 3GPP-specified radio channel models including path loss, shadowing and fast fading effects. The considered positioning approach exploits measurement of Time-Of-Arrival (TOA) and Angle-Of-Departure (AOD), which are estimated from beamformed NR synchronization signals. Based on the given measurements and the assumed train movement model, the train position is tracked by using an Extended Kalman Filter (EKF), which is able to handle the non-linear relationship between the TOA and AOD measurements, and the estimated train position parameters. It is shown that in the considered scenario the TOA measurements are able to achieve better accuracy compared to the AOD measurements. However, as shown by the results, the best tracking performance is achieved, when both of the measurements are considered. In this case, a very high, sub-meter, tracking accuracy can be achieved for most (>75%) of the tracking time, thus achieving the positioning accuracy requirements envisioned for the 5G NR. The pursued high-accuracy and high-availability positioning technology is considered to be in a key role in several envisioned HST use cases, such as mission-critical autonomous train systems.Comment: 6 pages, 5 figures, IEEE WCNC 2018 (Wireless Communications and Networking Conference