A novel TOA estimation method with effective NLOS error reduction

It is well known that non-line-of-sight （NLOS） error has been the major factor impeding the enhancement of accuracy for time of arrival （TOA） estimation and wireless positioning. This article proposes a novel method of TOA estimation effectively reducing the NLOS error by 60%, comparing with the traditional timing and synchronization method. By constructing the orthogonal training sequences, this method converts the traditional TOA estimation to the detection of the first arrival path （FAP） in the NLOS multipath environment, and then estimates the TOA by the round-trip transmission （RTT） technology. Both theoretical analysis and numerical simulations prove that the method proposed in this article achieves better performance than the traditional methods.

Effects of transmitter-related parameter settings on ranging accuracy for IR-UWB systems

For impulse radio ultra-wideband (IR-UWB) ranging systems,effects of the settings of transmitter-related parameters, which include the pulse shape, the bandwidth and the pulse repetition interval (PRI), on ranging accuracy were studied through theoretical analysis and simulations. Both the match-filtering based coherent TOA estimation algorithm and the energy-detection based non-coherent algorithm were used during simulations. Results show that the pulse shape has the least effect on the ranging accuracy. Increasing the pulse bandwidth can improve the ranging performance, but the performance is hardly improved any more when the bandwidth is increased beyond a certain level. PRI should be set long enough to guarantee the accurate ranging, because when PRI is shorter than the maximum excess delay of the channel, the ranging accuracy will be deteriorated by inter-pulse interference.

TDOA Localization Algorithm with Compensation of Clock Offset for Wireless Sensor Networks

This paper presents a source localization algorithm based on the source signal's time-difference-of-arrival(TDOA) for asynchronous wireless sensor network.To obtain synchronization among anchors,all anchors broadcast signals periodically,the clock offsets and skews of anchor pairs can be estimated using broadcasting signal's time-of-arrivals(TOA) at anchors.A kalman filter is adopted to improve the accuracy of clock offsets and track the clock drifts due to random fluctuations.Once the source transmits signal,the TOAs at anchors are stamped respectively and source's TDOA error due to clock offset and skew of anchor pair can be mitigated by a compensation operation.Based on a Gaussian noise model,maximum likelihood estimation(MLE) for the source position is obtained.Performance issues are addressed by evaluating the Cramer-Rao lower bound and the selection of broadcasting period.The proposed algorithm is simple and effective,which has close performance with synchronous TDOA algorithm.