A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> 4) Fingerprinting: <s> Application of antenna array processing has been suggested for mobile communication systems to overcome the problem of limited channel bandwidth and to satisfy an ever growing demand that the large number of mobiles put on the channel. Application of the array processing requires either a knowledge of a reference signal or the direction of the desired signal source to achieve its desired objectives. There exists a range of schemes to estimate the direction of arrival with conflicting demands of accuracy and processing power. This paper provides a tutorial treatment of direction-of-arrival estimation schemes covering a review of many existing direction-of-arrival (DOA) estimation methods including their performance, sensitivities and limitations. <s> BIB001 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> 4) Fingerprinting: <s> Node self-localization is a key research topic for wireless sensor networks (WSNs). There are two main algorithms, the triangulation method and the maximum likelihood (ML) estimator, for angle of arrival (AOA) based self-localization. The ML estimator requires a good initialization close to the true location to avoid divergence, while the triangulation method cannot obtain the closed-form solution with high efficiency. In this paper, we develop a set of efficient closed-form AOA based self-localization algorithms using auxiliary variables based methods. First, we formulate the self-localization problem as a linear least squares problem using auxiliary variables. Based on its closed-form solution, a new auxiliary variables based pseudo-linear estimator (AVPLE) is developed. By analyzing its estimation error, we present a bias compensated AVPLE (BCAVPLE) to reduce the estimation error. Then we develop a novel BCAVPLE based weighted instrumental variable (BCAVPLE-WIV) estimator to achieve asymptotically unbiased estimation of locations and orientations of unknown nodes based on prior knowledge of the AOA noise variance. In the case that the AOA noise variance is unknown, a new AVPLE based WIV (AVPLE-WIV) estimator is developed to localize the unknown nodes. Also, we develop an autonomous coordinate rotation (ACR) method to overcome the tangent instability of the proposed algorithms when the orientation of the unknown node is near π/2. We also derive the Cramer-Rao lower bound (CRLB) of the ML estimator. Extensive simulations demonstrate that the new algorithms achieve much higher localization accuracy than the triangulation method and avoid local minima and divergence in iterative ML estimators. <s> BIB002 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> 4) Fingerprinting: <s> Subspace-based source localization methods utilize the spectral magnitude of the MUltiple SIgnal Classification (MUSIC) method. However, in all these methods, a large number of sensors are required to resolve closely spaced sources. A novel method for high resolution source localization based on the group delay of MUSIC is described in this work. The method can resolve both the azimuth and elevation angles of closely spaced sources using a minimal number of sensors over a planar array. At the direction of arrival (DOA) of the desired source, a transition is observed in the phase spectrum of MUSIC. The negative differential of the phase spectrum also called group delay, results in a peak at the DOA. The proposed MUSIC-Group delay spectrum defined as product of MUSIC-Magnitude (MM) and group delay spectra, resolves spatially close sources even under reverberation owing to its spatial additive property. This is illustrated by performing spectral analysis of the MUSIC-Group delay function under reverberant environments. A mathematical proof for the spatial additive property of group delay spectrum is also provided. Source localization error analysis, sensor perturbation analysis, and Cramer-Rao bound (CRB) analysis are then performed to verify the robustness of the MUSIC-Group delay method. Experiments on speech enhancement and distant speech recognition are also conducted on spatialized TIMIT and MONC databases. Experimental results obtained using objective performance measures and word error rates (WER) indicate reasonable robustness when compared to conventional source localization methods in literature. <s> BIB003 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> 4) Fingerprinting: <s> In this paper, we target single-anchor localization schemes for millimeter wave (MMW) systems. The schemes are designed to be lightweight, so that even computationally-constrained devices can support them. We identify the main propagation properties of MMW signals that have an impact on localization and design three algorithms that exploit these, namely a triangulation-validation procedure, an angle difference-of-arrival approach, and a scheme based on location fingerprinting. We evaluate the algorithms by means of simulations, and draw conclusions on their robustness. We then validate our results via measurements involving commercial pre- standard 60- GHz MMW hardware. Our experiments confirm that, by relying only on a single anchor and without requiring complex signal processing at the receiver, the algorithms can localize a node with high probability, and in many cases with sub-meter accuracy. We conclude by discussing how these algorithms complement each other in terms of robustness and localization success probability. <s> BIB004 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> 4) Fingerprinting: <s> A general theoretical framework for Fingerprinting Localization Algorithms (FPS), given their popularity, can be utilized for their performance studies. In this work, after setting up an abstract model for FPS, it is shown that fingerprinting-based localization problem can be cast as a hypothesis testing (HT) problem and therefore various results in HT literature can be used to provide insights, guidelines and performance bounds for general FPS. This framework results in characterization of scaling limits of localization reliability in terms of number of measurements and other environmental parameters. It is suggested that Kullback-Leibler (KL) divergence between probability distributions of selected feature for fingerprinting at different locations encapsulates information about both accuracy and latency and can be used as a central performance metric for studying FPS. Although developed for an arbitrary fingerprint, the framework is particularly used for studying simple Received Signal Strength (RSS)- based algorithm. The effect of various parameters on the performance of fingerprinting algorithms is discussed, which includes path loss and fading characteristics, number of measurements at each point, number of anchors and their position, and placement of training points. Representative simulations and experimentation are used to verify validity of the theoretical frameworks in realistic setups. <s> BIB005 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> 4) Fingerprinting: <s> A growing number of sensors on smart mobile devices has led to rapid development of various mobile applications using location-based or context-aware services. Typically, outdoor localization techniques have relied on GPS or on cellular infrastructure support. While GPS gives high positioning accuracy, it can quickly deplete the battery on the device. On the other hand, base station based localization has low accuracy. In search of alternative techniques for outdoor localization, several approaches have explored the use of data gathered from other available sensors, like accelerometer, microphone, compass, and even daily patterns of usage, to identify unique signatures that can locate a device. Signatures, or fingerprints of an area, are hidden cues existing around a user's environment. However, under different operating scenarios, fingerprint-based localization techniques have variable performance in terms of accuracy, latency of detection, battery usage. The main contribution of this survey is to present a classification of existing fingerprint-based localization approaches which intelligently sense and match different clues from the environment for location identification. We describe how each fingerprinting technique works, followed by a review of the merits and demerits of the systems built based on these techniques. We conclude by identifying several improvements and application domain for fingerprinting based localization. <s> BIB006 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> 4) Fingerprinting: <s> Indoor localization has been an active research field for decades. Location determination is normally accomplished using the Global Positioning System (GPS) for outdoor environment. For indoor environment GPS does not work due to the lack of the sight line to satellite. Several technologies are deployed to construct an efficient indoor positioning system. A compromise between cost, accuracy and time deployment should be taken into account while choosing the best system. Most indoor localization approaches adopt WLAN as the basic schema of localizing due to many advantages. This paper gives an overview of indoor localization technologies, methods and performance metrics, and makes benchmark of existing solutions of Wi-Fi fingerprinting technique with detailed presentation of performances and limitations related to most important recent advances. <s> BIB007 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> 4) Fingerprinting: <s> Wireless Local Area Network (WLAN) has become a promising choice for indoor positioning as the only existing and established infrastructure, to localize the mobile and stationary users indoors. However, since WLAN has been initially designed for wireless networking and not positioning, the localization task based on WLAN signals has several challenges. Amongst the WLAN positioning methods, WLAN fingerprinting localization has recently achieved great attention due to its promising results. WLAN fingerprinting faces several challenges and hence, in this paper, our goal is to overview these challenges and the state-of-the-art solutions. This paper consists of three main parts: 1) Conventional localization schemes; 2) State-of-the-art approaches; 3) Practical deployment challenges. Since all the proposed methods in WLAN literature have been conducted and tested in different settings, the reported results are not equally comparable. So, we compare some of the main localization schemes in a single real environment and assess their localization accuracy, positioning error statistics, and complexity. Our results depict illustrative evaluation of WLAN localization systems and guide to future improvement opportunities. <s> BIB008
Fingerprinting approach is based on the fact that radio waves emitted from the base stations leave a unique radio fingerprint at a given location that can be used for localization BIB004 . The radio fingerprint is obtained by creating a database of the average values of RSS from various anchors at different locations. This requires a training phase to collect the fingerprints at known locations which can be used for the localization of the user based on probabilistic or deterministic positioning techniques, e.g., maximum likelihood estimator or k-nearest-neighbor estimator. Presently, most of the indoor localization methods are based on fingerprint matching technology BIB005 . Researchers have employed different methods to make fingerprint matching technology better in all aspects. As compared to other localization systems, Wi-Fi fingerprint positioning technology is cheap and has great precision. Owing to the vast deployment and use of Wi-Fi all over the world, fingerprint positioning technology can be used in any indoor environment where Wi-Fi networks are established, without the installation of extra hardware. In a complicated indoor scenario, under harsh conditions, the space-time traits such as angle and time of arrival can be erroneous, but the signal intensity is relatively stable. Therefore, it makes the accuracy of fingerprinting-based localization higher than other techniques. Fingerprinting based positioning systems are reviewed comprehensively in BIB006 , BIB008 , BIB007 . 5) Direction of Arrival (DoA) Technique: DoA ranging measurements are based on the angle of the received signal at the receiver BIB002 . The DoA-based approaches are simpler than time-based techniques because only two angle measurements are required to estimate the two-dimensional position. However, obtaining the accurate DoA-based ranges is a challenging task, especially in NLoS conditions. Moreover, in the indoor environments where the LoS signal is hard to obtain, DoA measurements are highly erroneous. DoA based techniques are classified into the following two categories based on the applications: • Online DoA: These techniques have lower complexity and are used for applications which require real time location information. In online DoA method, the angles are determined from the received signals and by using geometrical relationship (tri-angulation) between the anchors' position and the source position, the location of the source is estimated. • Offline DoA: These techniques have high complexity and can only be used for offline applications. Offline DoA is similar to the fingerprinting technique, where the DoA measurements are calculated multiple times and the average value is designated as the fingerprint. The source then locates itself by using these fingerprints by using triangulation. Online DoA is used in applications where high precision is not important such as beam-forming and signal detection BIB001 . Localization applications need accurate DoA estimation, even if it is not online. In comparison to other ranging techniques, DoA is more accurate, but consume high power and have greater complexity BIB003 .