A Method To Enhance Ranging Resolution For Localization Of Lora Sensors

In general, the Low Power Wide Area Internet-of-Things (IoT) wireless sensor networks operate in very narrow radio channels. This causes huge ambiguity when time-difference-of-arrival (TDoA) is used for localization of the sensors. To reduce this ambiguity we propose a solution which, without signal oversampling, approaches the Cramer-Rao lower bound (CRLB) in additive white noise for all useful signal-to-noise ratios (SNRs) by separating estimation of timestamps in two stages. First, the receiver cross-correlates the low bandwidth signal to determine a coarse timestamp estimate. Second, to fine-tune the coarse estimate, the same narrow band signal is correlated again with its template having much higher time granularity, but only over a narrow interval around the coarse estimate. Further improvement is achieved if the signal is oversampled just enough to accommodate for its slight frequency offset before the consecutive correlations.