A Holistic Approach to Guarantee the Reliability of Positioning Based on Carrier Phase for Indoor Pseudolite

The integrity monitoring algorithm based on pseudorange observations has been widely used outdoors and plays an important role in ensuring the reliability of positioning. However, pseudorange observations are greatly affected by the error sources such as multipath, clock drift, and noise in indoor pseudolite system, thus the pseudorange observations cannot be applied to high-precision indoor positioning. In general, double differenced (DD) carrier phase observations are used to obtain a high-precision indoor positioning result. What’s more, the carrier phase-based integrity monitoring (CRAIM) algorithm is applied to identify and exclude potential faults of the pseudolites. In this article, a holistic method is proposed to ensure the accuracy and reliability of positioning results. Firstly, if the reference pseudolite operates normally, extended Kalman filter is used for parameter estimation on the premise that the number of common pseudolites meets positioning requirements. Secondly, the innovation sequence in the Kalman filter is applied to construct test statistics and the corresponding threshold is determined from the Chi distribution with a given probability of false alert. The pseudolitehorizontal protection level (HPL) is calculated by the threshold and a prior probability of missed detection. Finally, compared the test statistics with the threshold to exclude the faultypseudolite for the reliability of positioning. The experiment results show that the proposed method improves the accuracy and stability of the results through faults detection and exclusion. This method ensures accuracies at the centimeter level for dynamic experiments and millimeter levels for static ones.

Improved Spectrum Sensing Based on Polar Codes for Cognitive Radio Networks

One challenge of a sensing technique is reducing sensing time while ensuring good effective data rate. In fact, once compressive sensing based on sub-Nyquist sampling is adopted, sensing time can be reduced by saving number of samples. This increases the probability of missed detection which causes collisions with primary service and worsens channel imperfections. In such case erasures occur in addition to errors. In this chapter, the authors propose a new technique to correct erasures while keeping sensing time at a desired level. Based on polar code and low complexity decoding algorithm, the proposed technique exhibits for high code rates better performance in terms of bit error rate (BER) compared to two existing techniques based on other codes, namely low-density parity check (LDPC) and BCH.