This work proposes the use of a hybrid acoustic and optical indoor positioning system for the accurate 3D positioning of Unmanned Aerial Vehicles (UAVs). The acoustic module of this system is based on a Time-Code Division Multiple Access (T-CDMA) scheme, where the sequential emission of five spread spectrum ultrasonic codes is performed to compute the horizontal vehicle position following a 2D multilateration procedure. The optical module is based on a Time-Of-Flight (TOF) camera that provides an initial estimation for the vehicle height. A recursive algorithm programmed on an external computer is then proposed to refine the estimated position. Experimental results show that the proposed system can increase the accuracy of a solely acoustic system by 70–80% in terms of positioning mean square error.

Acoustic local positioning systems (ALPSs) are an interesting alternative for indoor positioning due to certain advantages over other approaches, including their relatively high accuracy, low cost, and room-level signal propagation. Centimeter-level or fine-grained indoor positioning can be an asset for robot navigation, guiding a person to, for instance, a particular piece in a museum or to a specific product in a shop, targeted advertising, or augmented reality. In airborne system applications, acoustic positioning can be based on using opportunistic signals or sounds produced by the person or object to be located (e.g., noise from appliances or the speech from a speaker) or from encoded emission beacons (or anchors) specifically designed for this purpose. This work presents a review of the different challenges that designers of systems based on encoded emission beacons must address in order to achieve suitable performance. At low-level processing, the waveform design (coding and modulation) and the processing of the received signal are key factors to address such drawbacks as multipath propagation, multiple-access interference, near-far effect, or Doppler shifting. With regards to high-level system design, the issues to be addressed are related to the distribution of beacons, ease of deployment, and calibration and positioning algorithms, including the possible fusion of information obtained from maps and onboard sensors. Apart from theoretical discussions, this work also includes the description of an ALPS that was implemented, installed in a large area and tested for mobile robot navigation. In addition to practical interest for real applications, airborne ALPSs can also be used as an excellent platform to test complex algorithms (taking advantage of the low sampling frequency required), which can be subsequently adapted for other positioning systems, such as underwater acoustic systems or ultrawideband radio-frequency (UWB RF) systems.

The aim of this work is to propose an alternative way for wine classification and prediction based on an electronic nose (e-nose) combined with Independent Component Analysis (ICA) as a dimensionality reduction technique, Partial Least Squares (PLS) to predict sensorial descriptors and Artificial Neural Networks (ANNs) for classification purpose. A total of 26 wines from different regions, varieties and elaboration processes have been analyzed with an e-nose and tasted by a sensory panel. Successful results have been obtained in most cases for prediction and classification.

Golay sequences and complementary sets of sequences have been long studied for their application in multisensor and communication systems. The feasibility of these systems strongly depends on the design of an efficient generator and correlator with the aim of reducing the computational load and hardware complexity. Recursive algorithms, which allow efficient architectures, are available in the case of complementary pairs of sequences and complementary sets of four sequences. This work presents a generalization of these algorithms with the purpose of obtaining complementary sets of M sequences with length L, the number of sequences M being a power of two (M=2^m), and the length L a power of M (L=2^mN) with m,Nisin N-{0}. This fact allows an ideal Kroumlnecker delta function of weight MmiddotL in the addition of the autocorrelation functions of the M sequences of the set. Furthermore, the generation of M different mutually orthogonal sets can be obtained. This fact makes their application suitable in simultaneous multiemission systems. With the proposed algorithm, an effective reduction in the number of operations necessary to implement the correlator can be obtained, if it is compared with the straightforward implementation. Also, a regular structure is provided that allows implementation of the generator and/or the correlator for complementary sets of M sequences, based on the structure for complementary sets of M/2 sequences The sequence length can also be easily extended to any multiple of M. Finally, the generation and correlation of M different mutually orthogonal complementary sets of M sequences can be immediately derived