Hai Zhan

Impulse radio ultra-wideband ranging based on maximum likelihood estimation

We propose a high-resolution ranging algorithm for impulse radio (IR) ultra-WideBand (UWB) communication systems in additive white Gaussian noise. We formulate the ranging problem as a maximum- likelihood (ML) estimation problem for the channel delays and amplitudes at the receiver. Then we translate the obtained delay estimates into an estimate of the distance. The ML estimation problem is a non-linear problem and is hard to solve. Some previous works focus on finding alternative estimation procedures, for example by denoising. In contrast, we tackle the ML estimation problem directly. First, we use the same transformation as the first step of Iterative quadratic maximum likelihood (IQML) and we transform the ML problem into another optimization problem that avoids the estimation of the amplitude coefficients. Second, we solve the remaining optimization problem with a gradient descent approach (pseudo-quadratic maximum likelihood (PQML) algorithm). To demonstrate the good performance of the proposed estimator, we present the numerical evaluations under the IEEE 802.15.4a channel model. We show that our algorithm performs significantly better than previously published heuristics. We also derive a reduced complexity version of the algorithm algorithm, which will be implemented on the Xinlix field-programmable gate array (FPGA) board in the future. We test the approach in a real weak line of sight (LOS) propagation environment and obtained good accuracy for the ranging.

Theoretical Limit of Impulse Radio Ultra-WideBand TOA Positioning and TDOA Positioning

In this paper, we derive the Ziv-Zakai lower bounds for Impulse Radio (IR) Ultra-WideBand (UWB) Time Of Arrival (TOA)-based positioning and Time Difference Of Arrival (TDOA)-based positioning error based on geometry of indoor environments. We present the numerical evaluations with IEEE 802.15.4a channel model and the geometry of indoor environments of interest. As our derived bounds depend on the geometry of the indoor environments, our bounds can also be used in real environments with the channel measurements from real environments.

Impulse Radio Ultra-Wideband Ranging under Multi-User Environments

Practical impulse radio ultra-wideband (IR-UWB) ranging systems always have to work in multi-user and weak non-line-of-sight (NLOS) environments. In this paper, we derive a novel IR-UWB ranging estimator under multi-user and weak NLOS environments. We model MUI with complex Gaussian mixture model (CGMM) in the frequency domain. We propose a novel estimator for the UWB time of arrival (ToA) parameters based on the expectation maximization (EM) algorithm, the pseudo quadratic maximum likelihood (PQML) algorithm and CGMM. The estimator reduce the MUI in the frequency domain so that the cost function becomes asymptotically noiseless. Ranging is obtained by translating the obtained delay estimates into an estimate of the distance. And numerical evaluations under IEEE 802.15.3a channel model are presented to demonstrate the good performance of the proposed estimator.

One step Impulse Radio Ultra-WideBand positioning algorithm

We consider the problem of positioning estimation with Impulse Radio (IR) Ultra-WideBand (UWB) radio under dense multipaths and additive Gaussian noise environments. Most popular positioning algorithms first estimate certain parameters (such as Time of Arrival (TOA), Angle of Arrival (AOA) and Time Difference of Arrival (TDOA)) from the received signals. These parameters are then used to estimate the targeted position. In practice, the estimation of these parameters is not errors free and the distribution of the errors is difficult to model exactly. In contrast, we propose a novel one-step approach, which estimates the position and channels directly and jointly from the received signals of the used base stations. We use a Bayesian approach where the prior distribution of the channels follows the IEEE 802.15.4a channel model to estimate the joint posterior probability density function (pdf) of the channels, the targeted position and the transmit time. One application of the joint posterior pdf of the channels, the targeted position and the transmit time is the position determination with classical posterior estimator (such as Minimum Mean Square Error estimator (MMSE)). For computing the joint posterior pdf of the channels, the targeted position and the transmit time, we derived an algorithm which is based on sampling-importance resampling and the expectation maximization technique. Furthermore, we propose a reduced-complexity architecture of the proposed IR UWB localization system using our proposed algorithm. The algorithm can be easily implemented on hardware. Numerical evaluations under the IEEE 802.15.4a channel model are presented to demonstrate the good performance of the proposed estimator.

A Novel Bayesian Impulse Radio Ultra-WideBand Ranging Algorithm Based on Importance Sampling

We consider the problem of ranging with Impulse Radio (IR) Ultra-WideBand (UWB) radio under weak Line Of Sight (LOS) environments and additive Gaussian noise. We use a Bayesian approach where the prior distribution of the channel follows the IEEE 802.15.4a channel model, to estimate the joint posterior probability density function (pdf) of the channel and the targeted distance. One of applications of the joint posterior pdf of the channel and the targeted distance is the ranging determination with classical posterior estimators (such as Minimum Mean Square Error Estimator (MMSE)). For computing the joint posterior pdf of the channel and the targeted distance, we derived a novel algorithm which is based on importance sampling and expectation maximum techniques. Furthermore, we propose a reduced-complexity architecture of IR UWB ranging system using our proposed algorithm. The complexity analysis of the algorithm shows the proposed algorithm is a low-complexity one. Numerical evaluations under the IEEE 802.15.4a channel model are presented to demonstrate the good performance of the proposed estimator.

Statistical analysis of Impulse Radio Ultra-Wideband multi-user interference based on measurments

Multiuser interference (MUI) statistical models for impulse radio ultra-wideband (IR-UWB) systems can be an important in providing an accurate estimate of the channel state. As such, it can have a major impact on the overall system performance. In the literature, MUI in the time domain is often approximated with Middleton class A and Gaussian mixture models. We use measurements from an IR-UWB testbed under office Line of Sight (LOS) environments to assess the validity of these models. We also analysis the statistical properties of MUI in the frequency domain. We expect these findings to form the basis for useful interference models.

Ziv-Zakai Lower Bound for Impulse Radio Ultra-WideBand Ranging Error Correlation Matrix

We derive the Ziv-Zakai lower bound for Impulse Radio (IR) Ultra-WideBand (UWB) ranging error correlation matrix under a classical IR-UWB positioning system. We present the numerical evaluations with IEEE 802.15.4a channel model and the geometry of indoor environments of interest. As our derived bound depends on the geometry of the indoor environments, our bound can be used in real environments with the channel measurements from real environments.

Novel algorithms on Impulse Radio Ultra-WideBand ranging

We consider the problem of ranging with Impulse Radio (IR) Ultra-WideBand (UWB) radio under dense multipaths propagation environments and additive Gaussian noise. We propose a Bayesian detection algorithm where the prior distribution of the channel follows the IEEE 802.15.4a channel model, to identify whether the received signal is a Line-of-Sight (LOS) signal or a Non-Line-of-Sight (NLOS) signal. If it is a LOS signal, we use a Bayesian estimation approach to estimate the joint posterior probability density function (pdf) of the channel and the targeted distance. One of applications of the joint posterior pdf of the channel and the targeted distance is the ranging determination with classical posterior estimators (such as Minimum Mean Square Error Estimator (MMSE)). For computing the joint posterior pdf of the channel and the targeted distance, we derived a novel algorithm which is based on importance sampling and expectation maximum techniques. Numerical evaluations under the IEEE 802.15.4a channel model are presented to demonstrate the good performance of the proposed algorithms.

Maximum Likelihood time of arrival estimation for ultrawideband signals

In this contribution, we investigate maximum likelihood (ML) techniques for the estimation of time of arrival (ToA) for ultrawideband (UWB) propagation signals. Using the same methodology as [1], which was introduced for the multichannel estimation, we derive the ML criteria for the UWB ToA parameters estimation and we apply a denoising frequency-domain procedure so that the ML cost function becomes asymptotically noiseless. We show how the pseudo-quadratic ML (PQML), which is naturally asymptotically denoised, can be applied in the case of UWB time delays estimation and prove its convergence to the ML minimizer. Since the evaluation of the first time delay estimate can be converted to a distance estimate, the proposed method can be used for UWB ranging purposes and its optimal performance will hence follow for the UWB ranging accuracy. Simulation results are presented to demonstrate the good performance of the proposed techniques.