6 research outputs found
Long-Range Indoor Emitter Localization from 433MHz and 2.4GHz WLAN Received Signal Strengths
An improved search method for localizing a radio emitter in a building from its signal strength is proposed and implemented. It starts from floor level determination, which samples the signal strength on each floor and determines the floor level of the emitter. Then the search is conducted iteratively on a specific floor. For each round of search, one-dimensional (1-D) or two-dimensional (2-D) signal strength is collected according to the actual structure of the floor. The signal strength data are processed to fit a 1-D curve or a 2-D surface with regression models to establish an indicator or trend, which can either locate the emitter or provide direction for the next round of search. The main contribution of this thesis is that the data processing results for 2- D signal strength data can locate the emitter or show the direction of the emitter through gradient, which is helpful to future search. Our approach has been implemented with two wireless protocols: 433MHz protocol and 2.4GHz wireless local area network (WLAN) protocol. A 433MHz module with LoRa modulation is chosen to provide long propagation distance. A 2.4GHz WLAN tester is used for close range search where 433MHz signal does not show enough attenuation spread to be effective. 433MHz implementation consists of an emitter, a radio tester and an Android APP on a smartphone. The emitter is a board with an Arduino Uno and a 433MHz transceiver. The radio tester is a board with an Arduino Uno, a 433MHz transceiver and a Bluetooth-to-serial module to communicate with a smartphone. The radio tester and the APP work together to localize the emitter. 2.4GHz WLAN implementation is composed of an emitter, which is emulated with a smartphone, a radio tester which consists of a smartphone, and a router and two Android APPs. Both phones are connected through the router and socket communication is initiated with the radio tester working as a server and the emitter working as a client. The APP on the emitter implements the client functions. The radio tester controls data acquisition process. The APP on the tester establishes the server functions and deals with received data. It compares signal strengths in different locations and finds the position that has the strongest signal strength to locate the emitter. The innovative idea of this thesis is to use 1-D and 2-D signal strength with regression models as it is convenient to provide location or unique search direction of the emitter. 1-D data is processed with linear and polynomial regressions to fit curves in order to find possible location of the emitter in either a narrow strip or a half a plane. 2-D data is processed with multiple regressions to fit contour-line surfaces in order to find either location of the emitter on the top of a surface or a unique search direction of the location of the emitter as indicated by the highest surface gradient. Our approach is compared with the centroid algorithm with an example. The centroid algorithm assumes the emitter is located in the search area and it is also easily influenced by sampling location biases. Our approach has two advantages over the centroid algorithm. The first advantage is that our approach can work even when the emitter is out of the initial search area since it searches iteratively. The second advantage is that when the emitter is in the initial search area, our approach is not influenced by sampling location biases
Blind localization of radio emitters in wireless communications
The proliferation of wireless services is expected to increase the demand for radio spectrum in the foreseeable future. Given the limitations of the radio spectrum, it is evident that the current fixed frequency assignment policy fails to accommodate this increasing demand. Thus, the need for innovative technologies that can scale to accommodate future demands both in terms of spectrum efficiency and high reliable communication. Cognitive radio (CR) is one of the emerging technologies that offers a more flexible use of frequency bands allowing unlicensed users to exploit and use portions of the spectrum that are temporarily unused without causing any potential harmful interference to the incumbents. The most important functionality of a CR system is to observe the radio environment through various spectrum awareness techniques e.g., spectrum sensing or detection of spectral users in the spatio-temporal domain. In this research, we mainly focus on one of the key cognitive radio enabling techniques called localization, which provides crucial geo-location of the unknown radio transmitter in the surrounding environment. Knowledge of the user’s location can be very useful in enhancing the functionality of CRs and allows for better spectrum resource allocations in the spatial domain. For instance, the location-awareness feature can be harnessed to accomplish CR tasks such as spectrum sensing, dynamic channel allocation and interference management to enable cognitive radio operation and hence to maximize the spectral utilization. Additionally, geo-location can significantly expand the capabilities of many wireless communication applications ranging from physical layer security, geo-routing, energy efficiency, and a large set of emerging wireless sensor network and social networking applications. We devote the first part of this research to explore a broad range of existing cooperative localization techniques and through Monte-Carlo simulations analyze the performance of such techniques. We also propose two novel techniques that offer better localization performance with respect to the existing ones. The second and third parts of this research put forth a new analytical framework to characterize the performance of a particular low-complexity localization technique called weighted centroid localization (WCL), based on the statistical distribution of the ratio of two quadratic forms in normal variables. Specifically, we evaluate the performance of WCL in terms of the root mean square error (RMSE) and cumulative distribution function (CDF). The fourth part of this research focuses on studying the bias of the WCL and also provides solutions for bias correction. Throughout this research, we provide a case study analysis to evaluate the performance of the proposed approaches under changing channel and environment conditions. For the new theoretical framework, we compare analytical and Monte-Carlo simulation results of the performance metric of interest. A key contribution in our analysis is that we present not only the accurate performance in terms of the RMSE and CDF, but a new analytical framework that takes into consideration the finite nature of the network, overcoming the limitations of asymptotic results based on the central limit theorem. Remarkably, the numerical results unfold that the new analytical framework is able to predict the performance of WCL capturing all the essential aspects of propagation as well as the cognitive radio network spatial topology. Finally, we present conclusions gained from this research and possible future directions
Emitter Localization Using Received-Strength-Signal Data
This paper considers a scenario in which signals from an emitter at an unknown location are received at a number of different collinear locations. The receiver can determine the received signal strength, but no other parameters of the signal. Postulatin
RF signal sensing and source localisation systems using Software Defined Radios
Radio frequency (RF) source localisation is a critical technology
in numerous location-based military and civilian applications. In
this thesis, the problem of RF source localisation has been
studied from the perspective of the system implementation for
real-world applications. Commercial off-the-shelf Software
Defined Radio (SDR) devices are used to demonstrate the practical
RF source localisation systems. Compared to the conventional
localisation systems, which rely on dedicated hardware, the
SDR-based system is developed using general-purpose hardware and
software-defined components, offering great flexibility and cost
efficiency in system design and implementation.
In this thesis, the theoretical results of source localisation
are evaluated and put into practice. To be specific, the
practical localisation systems using different measurement
techniques, including received-signal-strength-indication (RSSI)
measurements, time-difference-of-arrival (TDOA) measurements and
joint TDOA and frequency-difference-of-arrival (FDOA)
measurements, are demonstrated to localise the stationary RF
signal sources using the SDRs. The RSSI-based localisation system
is demonstrated in small indoor and outdoor areas with a range of
several metres using the SDR-based transceivers. Furthermore,
interests from the defence area motivated us to implement the
time-based localisation systems. The TDOA-based source
localisation system is implemented using multiple spatially
distributed SDRs in a large outdoor area with the sensor-target
range of several kilometres. Moreover, they are implemented in a
fully passive way without prior knowledge of the signal emitter,
so the solutions can be applied in the localisation of
non-cooperative signal sources provided that emitters are
distant. To further reduce the system cost, and more importantly,
to deal with the situation when the deployment of multiple SDRs,
due to geographical restrictions, is not feasible, a joint TDOA
and FDOA-based localisation system is also demonstrated using
only one stationary SDR and one mobile SDR.
To improve the localisation accuracy, the methods that can reduce
measurement error and obtain accurate location estimates are
studied. Firstly, to obtain a better understanding of the
measurement error, the error sources that affect the measurement
accuracy are systematically analysed from three aspects: the
hardware precision, the accuracy of signal processing methods,
and the environmental impact. Furthermore, the approaches to
reduce the measurement error are proposed and verified in the
experiments. Secondly, during the process of the location
estimation, the theoretical results on the pre-existing
localisation algorithms which can achieve a good trade-off
between the accuracy of location estimation and the computational
cost are evaluated, including the weight least-squares
(WLS)-based solution and the Extended Kalman Filter (EKF)-based
solution. In order to use the pre-existing algorithms in the
practical source localisation, the proper adjustments are
implemented.
Overall, the SDR-based platforms are able to achieve low-cost and
universal localisation solutions in the real-world environment.
The RSSI-based localisation system shows tens of centimetres of
accuracy in a range of several metres, which provides a useful
tool for the verification of the range-based localisation
algorithms. The localisation accuracy of the TDOA-based
localisation system and the joint TDOA and FDOA-based
localisation system is several tens of metres in a range of
several kilometres, which offers potential in the low-cost
localisation solutions in the defence area