An Energy Efficient Time-Frequency Transformation of Chirp Signals in Multipath Channels for MUSIC-Based TOA Estimation

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Abstract

Range estimation based on time of arrival (TOA) is becoming increasingly important with the emergence of location-based applications and next-generation location-aware wireless sensor networks. For radar and positioning systems, chirp signals have primarily been used due to their inborn signal properties for decomposition. Recently, chirp signal has been selected as the baseline standard of ISO/IEC 24730-5 and IEEE 802.15.4a in 2.4GHz, organized for the development of a real-time accurate positioning system. When estimating the TOA of the received signals in multipath channel, the super-resolution algorithms, known as estimation of signal parameters via rotational invariance techniques (ESPRIT), multiple signal classification method (MUSIC) and matrix pencil (MP), are preferred due to their superiority in decomposing the received paths. For the super-resolution algorithm-based TOA estimation of chirp signals, the received chirp signals must be transformed into a sinusoidal form for the super-resolution algorithm. The conventional transformation, the de-chirping technique, changes the received chirp signals to sinusoids so that the super-resolution algorithms can estimate the TOA of the received chirp signals through a frequency estimation of the transformed sinusoids. In practice, the initial timing synchronizer at receiver tries to find the maximum energy point at which the received paths are overlapped maximally. At this time, the conventional de-chirping yields lossy transformed sinusoids for the first arrival path from the received samples synchronized to the maximum energy point. The first arrival path is not involved in the transformed sinusoids with the conventional transformation, leading to performance degradation. However, the proposed energy efficient time-frequency transformation achieves lossless transformation by using the extended reference chirp signals. The proposed transformation is incorporated with MUSIC-based TOA estimation. The effectiveness of the proposed transformation is analyzed and verified. The root mean squared error (RMSE) of the proposed transformation is compared with Cramer-Rao lower bound and those for the conventional algorithms such as super-resolution, ESPRIT and matrix pencil algorithm in multipath channel.

Journal

  • IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E98.A(8), 1769-1776, 2015

    The Institute of Electronics, Information and Communication Engineers

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