{"title":"直接测距在多径信道使用OFDM导频信号","authors":"Lishuai Jing, T. Pedersen, B. Fleury","doi":"10.1109/SPAWC.2014.6941350","DOIUrl":null,"url":null,"abstract":"OFDM ranging is becoming important for positioning using terrestrial wireless networks. Conventional ranging methods rely on a two-step approach: range related parameters, such as the time of arrival (TOA), the bias induced by non-line-of-sight (NLOS) propagations etc., are first estimated, based on which the range is then inferred. In multi-path conditions, two-step range estimators which employ the correlator-based estimator or the energy detector lead to poor ranging accuracy when applied in non-ultra-wideband scenarios due to bias. More advanced ranging schemes that estimate all multi-path components using a multidimensional search procedure provide higher ranging accuracy but have a prohibitive complexity. In this work, we propose a novel direct ranging technique that uses a point process formulated channel model. Based on this model, we derive an approximate maximum likelihood estimator of the range. In contrast to the estimator which requires a multidimensional search procedure, the proposed estimator does not demand the knowledge of the exact number of multi-path components and these components are separable. If the power delay spectrum of the multi-path channel and the signal-to-noise-ratio (SNR) are known, the complexity of the proposed estimator is tractable. We show by means of Monte Carlo simulations that this estimator outperforms the correlator-based estimator.","PeriodicalId":420837,"journal":{"name":"2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Direct ranging in multi-path channels using OFDM pilot signals\",\"authors\":\"Lishuai Jing, T. Pedersen, B. Fleury\",\"doi\":\"10.1109/SPAWC.2014.6941350\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"OFDM ranging is becoming important for positioning using terrestrial wireless networks. Conventional ranging methods rely on a two-step approach: range related parameters, such as the time of arrival (TOA), the bias induced by non-line-of-sight (NLOS) propagations etc., are first estimated, based on which the range is then inferred. In multi-path conditions, two-step range estimators which employ the correlator-based estimator or the energy detector lead to poor ranging accuracy when applied in non-ultra-wideband scenarios due to bias. More advanced ranging schemes that estimate all multi-path components using a multidimensional search procedure provide higher ranging accuracy but have a prohibitive complexity. In this work, we propose a novel direct ranging technique that uses a point process formulated channel model. Based on this model, we derive an approximate maximum likelihood estimator of the range. In contrast to the estimator which requires a multidimensional search procedure, the proposed estimator does not demand the knowledge of the exact number of multi-path components and these components are separable. If the power delay spectrum of the multi-path channel and the signal-to-noise-ratio (SNR) are known, the complexity of the proposed estimator is tractable. We show by means of Monte Carlo simulations that this estimator outperforms the correlator-based estimator.\",\"PeriodicalId\":420837,\"journal\":{\"name\":\"2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPAWC.2014.6941350\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPAWC.2014.6941350","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Direct ranging in multi-path channels using OFDM pilot signals
OFDM ranging is becoming important for positioning using terrestrial wireless networks. Conventional ranging methods rely on a two-step approach: range related parameters, such as the time of arrival (TOA), the bias induced by non-line-of-sight (NLOS) propagations etc., are first estimated, based on which the range is then inferred. In multi-path conditions, two-step range estimators which employ the correlator-based estimator or the energy detector lead to poor ranging accuracy when applied in non-ultra-wideband scenarios due to bias. More advanced ranging schemes that estimate all multi-path components using a multidimensional search procedure provide higher ranging accuracy but have a prohibitive complexity. In this work, we propose a novel direct ranging technique that uses a point process formulated channel model. Based on this model, we derive an approximate maximum likelihood estimator of the range. In contrast to the estimator which requires a multidimensional search procedure, the proposed estimator does not demand the knowledge of the exact number of multi-path components and these components are separable. If the power delay spectrum of the multi-path channel and the signal-to-noise-ratio (SNR) are known, the complexity of the proposed estimator is tractable. We show by means of Monte Carlo simulations that this estimator outperforms the correlator-based estimator.