This paper presents a new architecture for the correlation of orthogonal complementary sets of sequences (OCSS) and their performance in an ultrasonic local positioning system (U-LPS). OCSS are sets of sequences whose addition of correlation functions has ideal properties, that makes interference-free code-division multiple access (CDMA) possible. They can be used to encode the signals emitted by a CDMAbased U-LPS, enhancing the performance of such systems in terms of immunity against noise, multipath propagation, and near-far effect. Also, the orthogonality of the codes offers an operation resistance to multiaccess interference, which endows the U-LPS with the capability of simultaneous emission from different beacons. On the other hand, the detection of OCSS codes can be performed by means of efficient algorithms. This paper presents an optimization of previous proposals allowing the simultaneous correlation of OCSS by using fewer operations and memory elements. Furthermore, the hardware implementation of the proposed optimization is also addressed, and an U-LPS based on this proposal is presented.
In this work, an acoustic sensor network for a relative localization system is analyzed by reporting the accuracy achieved in the position estimation. The proposed system has been designed for those applications where objects are not restricted to a particular environment and thus one cannot depend on any external infrastructure to compute their positions. The objects are capable of computing spatial relations among themselves using only acoustic emissions as a ranging mechanism. The object positions are computed by a multidimensional scaling (MDS) technique and, afterwards, a least-square algorithm, based on the Levenberg-Marquardt algorithm (LMA), is applied to refine results. Regarding the position estimation, all the parameters involved in the computation of the temporary relations with the proposed ranging mechanism have been considered. The obtained results show that a fine-grained localization can be achieved considering a Gaussian distribution error in the proposed ranging mechanism. Furthermore, since acoustic sensors require a line-of-sight to properly work, the system has been tested by modeling the lost of this line-of-sight as a non-Gaussian error. A suitable position estimation has been achieved even if it is considered a bias of up to 25 of the line-of-sight measurements among a set of nodes.
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