Toward a unified PNT, Part 1: Complexity and context: Key challenges of multisensor positioning

The next generation of navigation and positioning systems must provide greater accuracy and reliability in a range of challenging environments to meet the needs of a variety of mission-critical applications. No single navigation technology is robust enough to meet these requirements on its own, so a multisensor solution is required. Known environmental features, such as signs, buildings, terrain height variation, and magnetic anomalies, may or may not be available for positioning. The system could be stationary, carried by a pedestrian, or on any type of land, sea, or air vehicle. Furthermore, for many applications, the environment and host behavior are subject to change. A multi-sensor solution is thus required. The expert knowledge problem is compounded by the fact that different modules in an integrated navigation system are often supplied by different organizations, who may be reluctant to share necessary design information if this is considered to be intellectual property that must be protected

Super-Resolution TOA Estimation with Diversity Techniques for Indoor Geolocation Applications

Recently, there are great interests in the location-based applications and the location-awareness of mobile wireless systems in indoor areas, which require accurate location estimation in indoor environments. The traditional geolocation systems such as the GPS are not designed for indoor applications, and cannot provide accurate location estimation in indoor environments. Therefore, there is a need for new location finding techniques and systems for indoor geolocation applications. In this thesis, a wide variety of technical aspects and challenging issues involved in the design and performance evaluation of indoor geolocation systems are presented first. Then the TOA estimation techniques are studied in details for use in indoor multipath channels, including the maximum-likelihood technique, the MUSIC super-resolution technique, and diversity techniques as well as various issues involved in the practical implementation. It is shown that due to the complexity of indoor radio propagation channels, dramatically large estimation errors may occur with the traditional techniques, and the super-resolution techniques can significantly improve the performance of the TOA estimation in indoor environments. Also, diversity techniques, especially the frequency-diversity with the CMDCS, can further improve the performance of the super-resolution techniques

Cramer-Rao bounds in the estimation of time of arrival in fading channels

This paper computes the Cramer-Rao bounds for the time of arrival estimation in a multipath Rice and Rayleigh fading scenario, conditioned to the previous estimation of a set of propagation channels, since these channel estimates (correlation between received signal and the pilot sequence) are sufficient statistics in the estimation of delays. Furthermore, channel estimation is a constitutive block in receivers, so we can take advantage of this information to improve timing estimation by using time and space diversity. The received signal is modeled as coming from a scattering environment that disperses the signal both in space and time. Spatial scattering is modeled with a Gaussian distribution and temporal dispersion as an exponential random variable. The impact of the sampling rate, the roll-off factor, the spatial and temporal correlation among channel estimates, the number of channel estimates, and the use of multiple sensors in the antenna at the receiver is studied and related to the mobile subscriber positioning issue. To our knowledge, this model is the only one of its kind as a result of the relationship between the space-time diversity and the accuracy of the timing estimation.Peer ReviewedPostprint (published version

A survey on acoustic positioning systems for location-based services

Positioning systems have become increasingly popular in the last decade for location-based services, such as navigation, and asset tracking and management. As opposed to outdoor positioning, where the global navigation satellite system became the standard technology, there is no consensus yet for indoor environments despite the availability of different technologies, such as radio frequency, magnetic field, visual light communications, or acoustics. Within these options, acoustics emerged as a promising alternative to obtain high-accuracy low-cost systems. Nevertheless, acoustic signals have to face very demanding propagation conditions, particularly in terms of multipath and Doppler effect. Therefore, even if many acoustic positioning systems have been proposed in the last decades, it remains an active and challenging topic. This article surveys the developed prototypes and commercial systems that have been presented since they first appeared around the 1980s to 2022. We classify these systems into different groups depending on the observable that they use to calculate the user position, such as the time-of-flight, the received signal strength, or the acoustic spectrum. Furthermore, we summarize the main properties of these systems in terms of accuracy, coverage area, and update rate, among others. Finally, we evaluate the limitations of these groups based on the link budget approach, which gives an overview of the system's coverage from parameters such as source and noise level, detection threshold, attenuation, and processing gain.Agencia Estatal de InvestigaciónResearch Council of Norwa

Enabling Technology and Algorithm Design for Location-Aware Communications

Location-awareness is emerging as a promising technique for future-generation wire­ less network to adaptively enhance and optimize its overall performance through location-enabled technologies such as location-assisted transceiver reconfiguration and routing. The availability of accurate location information of mobile users becomes the essential prerequisite for the design of such location-aware networks. Motivated by the low locationing accuracy of the Global Positioning System (GPS) in dense multipath environments, which is commonly used for acquiring location information in most of the existing wireless networks, wireless communication system-based po­sitioning systems have been investigated as alternatives to fill the gap of the GPS in coverage. Distance-based location techniques using time-of-arrival (TOA) mea­surements are commonly preferred by broadband wireless communications where the arrival time of the signal component of the First Arriving Path (FAP) can be con­verted to the distance between the receiver and the transmitter with known location. With at least three transmitters, the location of the receiver can be determined via trilatération method. However, identification of the FAP’s signal component in dense multipath scenarios is quite challenging due to the significantly weaker power of the FAP as compared with the Later Arriving Paths (LAPs) from scattering, reflection and refraction, and the superposition of these random arrival LAPs’ signal compo­ nents will become large interference to detect the FAP. In this thesis, a robust FAP detection scheme based on multipath interference cancellation is proposed to im­ prove the accuracy of location estimation in dense multipath environments. In the proposed algorithm, the signal components of LAPs is reconstructed based on the estimated channel and data with the assist of the communication receiver, and sub­ sequently removed from the received signal. Accurate FAP detection results are then achieved with the cross-correlation between the interference-suppressed signal and an augmented preamble which is the combination of the original preamble for com­ munications and the demodulated data sequences. Therefore, more precise distance estimation (hence location estimation) can be obtained with the proposed algorithm for further reliable network optimization strategy design. On the other hand, multiceli cooperative communication is another emerging technique to substantially improve the coverage and throughput of traditional cellular networks. Location-awareness also plays an important role in the design and imple­mentation of multiceli cooperation technique. With accurate location information of mobile users, the complexity of multiceli cooperation algorithm design can be dra­matically reduced by location-assisted applications, e.g., automatic cooperative base station (BS) determination and signal synchronization. Therefore, potential latency aroused by cooperative processing will be minimized. Furthermore, the cooperative BSs require the sharing of certain information, e.g., channel state information (CSI), user data and transmission parameters to perform coordination in their signaling strategies. The BSs need to have the capabilities to exchange available information with each other to follow up with the time-varying communication environment. As most of broadband wireless communication systems are already orthogonal frequency division multiplexing (OFDM)-based, a Multi-Layered OFDM System, which is spe­cially tailored for multiceli cooperation is investigated to provide parallel robust, efficient and flexible signaling links for BS coordination purposes. These layers are overlaid with data-carrying OFDM signals in both time and frequency domains and therefore, no dedicated radio resources are required for multiceli cooperative networks. In the final aspect of this thesis, an enhanced channel estimation through itera­ tive decision-directed method is investigated for OFDM system, which aims to provide more accurate estimation results with the aid of the demodulated OFDM data. The performance of traditional training sequence-based channel estimation is often lim­ ited by the length of the training. To achieve acceptable estimation performance, a long sequence has to be used which dramatically reduces the transmission efficiency of data communication. In this proposed method, the restriction of the training se­quence length can be removed and high channel estimation accuracy can be achieved with high transmission efficiency, and therefore it particular fits in multiceli coopera­tive networks. On the other hand, as the performance of the proposed FAP detection scheme also relies on the accuracy of channel estimation and data detection results, the proposed method can be combined with the FAP detection scheme to further optimize the accuracy of multipath interference cancellation and FAP detection

Human Sensing via Passive Spectrum Monitoring

Human sensing is significantly improving our lifestyle in many fields such as elderly healthcare and public safety. Research has demonstrated that human activity can alter the passive radio frequency (PRF) spectrum, which represents the passive reception of RF signals in the surrounding environment without actively transmitting a target signal. This paper proposes a novel passive human sensing method that utilizes PRF spectrum alteration as a biometrics modality for human authentication, localization, and activity recognition. The proposed method uses software-defined radio (SDR) technology to acquire the PRF in the frequency band sensitive to human signature. Additionally, the PRF spectrum signatures are classified and regressed by five machine learning (ML) algorithms based on different human sensing tasks. The proposed Sensing Humans among Passive Radio Frequency (SHAPR) method was tested in several environments and scenarios, including a laboratory, a living room, a classroom, and a vehicle, to verify its extensiveness. The experimental results show that the SHAPR method achieved more than 95% accuracy in the four scenarios for the three human sensing tasks, with a localization error of less than 0.8 m. These results indicate that the SHAPR technique can be considered a new human signature modality with high accuracy, robustness, and general applicability

INDOOR-WIRELESS LOCATION TECHNIQUES AND ALGORITHMS UTILIZING UHF RFID AND BLE TECHNOLOGIES

The work presented herein explores the ability of Ultra High Frequency Radio Frequency (UHF RF) devices, specifically (Radio Frequency Identification) RFID passive tags and Bluetooth Low Energy (BLE) to be used as tools to locate items of interest inside a building. Localization Systems based on these technologies are commercially available, but have failed to be widely adopted due to significant drawbacks in the accuracy and reliability of state of the art systems. It is the goal of this work to address that issue by identifying and potentially improving upon localization algorithms. The work presented here breaks the process of localization into distance estimations and trilateration algorithms to use those estimations to determine a 2D location. Distance estimations are the largest error source in trilateration. Several methods are proposed to improve speed and accuracy of measurements using additional information from frequency variations and phase angle information. Adding information from the characteristic signature of multipath signals allowed for a significant reduction in distance estimation error for both BLE and RFID which was quantified using neural network optimization techniques. The resulting error reduction algorithm was generalizable to completely new environments with very different multipath behavior and was a significant contribution of this work. Another significant contribution of this work is the experimental comparison of trilateration algorithms, which tested new and existing methods of trilateration for accuracy in a controlled environment using the same data sets. Several new or improved methods of triangulation are presented as well as traditional methods from the literature in the analysis. The Antenna Pattern Method represents a new way of compensating for the antenna radiation pattern and its potential impact on signal strength, which is also an important contribution of this effort. The performance of each algorithm for multiple types of inputs are compared and the resulting error matrix allows a potential system designer to select the best option given the particular system constraints