Emanuel Staudinger

Particle filter based positioning with 3GPP-LTE in indoor environments

Global navigation satellite systems (GNSSs) can deliver very good position estimates under optimum conditions. However, especially in urban and indoor scenarios with severe multipath propagation and blocking of satellites by buildings the accuracy loss can be very large. Often, a position with GNSS is impossible in these scenarios. On the other hand, cellular wireless communication systems such as the third generation partnership project (3GPP) long-term evolution (LTE) provide excellent coverage in urban and most indoor environments. Thus, this paper researches timing based positioning algorithms, in this case time difference of arrival (TDoA), using 3GPP-LTE measurements. Several approaches and algorithms exist to solve the navigation equation for cellular systems, for instance Bayes filtering methods such as Kalman or particle filter. This paper specifically considers and develops a particle filter for 3GPP-LTE TDoA positioning. To obtain better positioning results, a 3GPP-LTE TDoA error model is derived. This error model is afterwards included in the likelihood function of the particle filter. The last part of this paper, evaluates the positioning performances of the developed particle filter in an indoor scenario. These evaluations show clearly the possibility of using 3GPP-LTE measurements for indoor positioning.

Cooperative and heterogeneous indoor localization experiments

In this paper we present the results of real-life localization experiments performed in an unprecedented cooperative and heterogeneous wireless context. These measurements are based on ZigBee and orthogonal frequency division multiplexing (OFDM) devices, respectively endowed with received signal strength indicator (RSSI) and round trip delay (RTD) estimation capabilities. More particularly we emulate a multi-standard terminal, moving in a typical indoor environment, while communicating with fixed OFDM-based femto-base stations (Femto-BSs) and with other mobiles or fixed anchor nodes (through peer-to-peer links) forming a wireless sensor network (WSN). We introduce the measurement functionalities and metrics, the scenario and set-up, providing realistic connectivity and obstruction conditions. Out of the experimental data, preliminary positioning results based on cooperative and geometric algorithms are finally discussed, showing benefits through mobile-to-mobile cooperation, selective hybrid data fusion and detection of unreliable nodes.

Generic real-time round-trip-delay test-bed for cooperative positioning

This paper presents a concept for a generic mixed hardware/software test-bed to evaluate state of the art and future round-trip-delay ranging concepts and estimation algorithms. The system presented is mainly comprised of commercial-off-the-shelf components. It supports orthogonal frequency division multiplex (OFDM), direct sequence spread spectrum (DSSS) or chirp pulses. The test-bed gives us the flexibility to transfer estimation algorithms from theory directly to a prototype where we are free to choose between mixed MATLAB, field programmable gate array (FPGA) and software implementations. We give an insight view into the overall architecture, its properties, possibilities and limitations. Furthermore, we show link budget calculations and the expected performance with Cramér-Rao lower bounds (CRLB) for this system based on state-of-the-art OFDM block-type synchronization symbols which are also used in 3GPP-LTE.

Self-organized hybrid channel access method for an interleaved RTD-based swarm navigation system

Swarm navigation systems are emerging technique to investigate unknown environment. Organizing the access of shared radio channel is one of the main challenges due to the massive number of anarchical agents and the crucial mission requirements, e.g. update-rate and position accuracy. In this paper, we design a radio-based swarm navigation system and propose a pulse-coupled oscillators (PCO)-based self-organized method to access the shared channel. The channel is accessed with the time division multiple access (TDMA) scheme. The frequency division duplexing (FDD) method is built on top to solve the temporally hidden node problem. Distances are measured with the interleaved round trip delay (I-RTD) so that multiple measurements can be taken simultaneously and without the need of clock synchronization. It takes the realistic mission requirements and the physical radio effects into consideration. The simulation results show that a swarm bootstrapping task can be accomplished in a few seconds with our proposed system.

TDoA subsample delay estimator with multiple access interference mitigation and carrier frequency offset compensation for OFDM based systems

This paper presents a novel maximum likelihood (ML) time difference of arrival (TDoA) estimation algorithm for subsample delays. We introduce a new initial acquisition and cell search algorithm with implicit multiple access interference (MAI) cancelation. A joint carrier frequency offset (CFO) estimation and subsample delay estimation is used to compensate Doppler spreads and oscillator drifts. Analytical derivations show how the CFO influences the TDoA subsample delay estimation and vice versa. Furthermore, we show through numerical simulations that the geographic base station mapping and the used synchronization codes influence the estimation accuracy. Additionally, we introduce a new successive interference cancelation (SIC) to improve the overall accuracy.

Sparse subcarrier allocation for timing-based ranging with OFDM modulated signals in outdoor environments

Accurate range estimation is a fundamental and crucial part of any position estimation technique. State-of-the-art systems exploiting OFDM modulated signals use narrowband block-type synchronization symbols or a scattered pilot structure. These synchronization symbols are mainly designed to allow communication only. Their timing estimation performance is not sufficient for ranging and especially for any concurrent multi-user access for advanced ranging schemes. In this paper, we propose a new, deterministic subcarrier allocation method for OFDM-based ranging in outdoor environments. The resulting symbol can be exploited for concurrent multi-user ranging, e.g., for cooperative positioning of unmanned aerial vehicles (UAVs). We study theoretical performances with a Cramer-Rao lower-bound (CRLB) and the true performance with a Maximum-Likelihood (ML) estimator. The correlation function for the ML estimator changes with the sparse subcarrier allocation. This leads to peak ambiguities and therefore to a significant divergence between the ML estimator performance and the CRLB at higher sparsity levels and low signal to noise ratios. We propose a simple adaptive solution to resolve ambiguities and show that we can reach the CRLB with our adapted estimator again.

Round-trip delay indoor ranging experiments with OFDM signals

Ranging accuracy and reliability is crucial for any cooperative- and non-cooperative positioning system indoors. State of the art systems exploit received signal strength (RSS) from WiFi devices, or ultra-wide bandwidth (UWB) timing based range estimation. RSS proved to be unreliable in rich multipath environments. UWB combats multipath at the cost of high bandwidth and specialized hardware which is not integrated in state of the art mobile radio transceivers, e.g., in mobile phones. We tackle this problem with round-trip delay (RTD) based range estimation with orthogonal frequency division multiplex (OFDM) modulated signals which are widely used in WiFi and 3GPP-LTE. In this paper, we present our measurement setup, specifically the developed prototype and two different indoor environments with varying multipath conditions. Measurements along ground truth points are collected for each environment and post-processed. We apply four different estimators, two based on cross-correlation and interpolation, and two based on Maximum-likelihood (ML) multipath estimation. Furthermore, we analyze differences for each estimator in each measurement environment. This analysis reveals that a simple correlation based estimator with interpolation and smart thresholding is sufficient and a very good trade-off between computational complexity and accuracy compared to ML multipath estimators. These indoor experiments show that our simple ranging technique is suitable for indoor distance estimation with low bandwidth, low transmit power, and can be exploited for LTE Direct with low complexity.

Anchor-Free Localization using Round-Trip Delay Measurement for Martian Swarm Exploration

Robotic swarms are promising technique to explore infrastructure-less environments. Many researches in robotic swarm focus on the swarm control and assume an external source for the swarm location information. In this paper, we investigate the radio-based anchor-free localization problem for a robotic swarm. Formation is estimated collectively with only inter-agent distance measurements using the round-trip delay (RTD) technique. Fundamental limits, such as the lower bound of anchor-free localization, tracking and ranging are derived. We further investigate the connectivity and ranging accuracy trade-off with realistic radio resource characteristics. The local Cramér-Rao Bound (CRB) and posterior Cramér-Rao Bound (PCRB) approximations are used to calculate the equivalent ranging variance (ERV). The ERV is used for distributed assessing the reliability of neighbors location information and low complexity distributed anchor-free localization algorithms design. ERV-aided distributed Gauss-Newton algorithm (ERV-DGN) and ERV-aided distributed particle filter algorithm (ERV-DPF) are proposed to achieve robust anchor-free localization. Overlooking the ambiguity is a limitation of localization CRB. This problem can be avoided by controlling the number of simultaneous RTD links from the hearability range. The performance of the ERV-DPF with real measurement data shows a sub-meter accuracy level for anchor-free localization. Hence, accurate anchor-free localization for robotic swarm using radio RTD measurements is applicable and promising.

A generic OFDM based TDoA positioning testbed with interference mitigation for subsample delay estimation

This paper gives an introduction to a generic OFDM based testbed for positioning using time difference of arrival (TDoA) measurements. An overview of the transmitter system and receiver system is given. Furthermore an inital access algorithm with interference mitigation for subsample delay estimation is presented and simulation results are shown. The influence of the geographic base station mapping and the used synchronization codes is discussed. First measurement results reveal perliminary figures for the expected performance leading to further algorithm investigations.

Round-trip delay ranging with OFDM signals — Performance evaluation with outdoor experiments

Ranging accuracy and reliability is crucial for any cooperative- and non-cooperative positioning system applied for unmanned vehicle localization, and formation estimation. State of the art systems exploit received signal strength (RSS) from WiFi devices, or ultra-wide bandwidth (UWB) timing based range estimation. RSS proved to be unreliable in environments with multipath, and UWB combats multipath at the cost of high bandwidth and specialized hardware. We tackle this problem with round-trip delay (RTD) based range estimation with orthogonal frequency division multiplex (OFDM) modulated signals which are widely used in WiFi and 3GPP-LTE. In this paper, we present our developed prototype and two different outdoor environments with varying multipath conditions. Measurements along ground truth points are collected for each environment and post-processed. We apply four different estimators, two based on cross-correlation and interpolation, and two based on Maximum-likelihood (ML) multipath estimation. Our analysis reveals that a simple correlation based estimator with interpolation and smart thresholding is sufficient and a very good trade-off between computational complexity and accuracy compared to ML multipath estimators. These outdoor experiments show that our simple ranging technique is suitable for peer-to-peer distance estimation with low bandwidth, low transmit power, and can be exploited for localization and formation estimation in cyber-physical systems.