Direction finding of long term evolution enabled handsets for monitoring applications
Rossouw Van der Merwe · UpSpace Institutional Repository (University of Pretoria) · 2016
Given the widespread adoption of cellular-phones, it can be assumed that the presence of a phone can predict with good certainty the presence of a human being. Therefore the location of phones in restricted areas can aid in anti-poaching, anti-smuggling, illegal immigration, and search-and rescue operations. There are numerous obstacles associated with regulations and policies which restrict the direct use of the cellular network, therefore the acquisition of a non-network cooperative (NNC) direction finding (DF) receiver system is required. This dissertation addresses the development of such a NNC system. The system requirements for a NNC-DF is analysed to illustrate the design challenges, such as DF accuracy, dynamic range, inter-channel interference, processing requirements and cost. Theoretical analysis of different receiver designs, DF estimation algorithms, processing methods, and sensory input configurations, are done and investigated through simulation. The simulation results are used to optimise the system parameters in terms of processing time versus DF accuracy. The optimised results are then used to discuss the design process for an operational system. Several Multiple Signal Classification (MuSiC) based algorithms are used for the directionof- arrival (DOA) estimation, as these algorithms are super-resolution phase interferometry algorithms. Linear and circular sensor arrays of four to six elements are considered for the investigation. A selection of receivers which use different levels of signal isolation and integration methods are used and compared. The simulation results illustrate that receiver designs with high signal separation have superior results, but the associated processing requirements make these receivers impractical. Many of the simpler receiver architectures achieved competitive DF accuracy, and required only a fraction of the processing resources. Exploiting the resource block (RB) structure of Long-Term Evolution (LTE), the 12-carriers per RB can be combined to improve DF estimation. It was found that integration of the autocovariance matrix (ACM) of 12 carriers in a RB (MuSiC based algorithms require the ACM for estimation) yields the best results. The Root-MuSiC algorithm resulted in the optimal performance versus processing time for linear arrays, and the frequency-domain Root-MuSiC algorithm for circular arrays. Advanced forms of the MuSiC algorithm, which use the weighted least squares (WLS) algorithm, required additional processing, but results did not improve significantly. It was also found that the design of the receiver had a greater influence on the performance than the DF algorithms. Optimisation was done so as to find the best combination of the following: receiver design, integration method, windowing method, DF algorithm, antenna configuration and antenna size. The optimisation compared the processing time to DF accuracy of the different DF systems. It was shown that for uniform circular arrays (UCAs), simple receiver architectures with ACM integration over a RB, using a rectangular window and the frequency-domain (FD)- Root-MuSiC algorithm, yielded the best processing time versus DF accuracy. Similar results were found with uniform linear arrays (ULAs), with the exception that the Root-MuSiC algorithm performed better. Optimisation proved efficient DF receiver design. It was concluded that the best possible DF accuracy often requires an impractical system. Similarly, arbitrary large arrays yield excellent results, but are expensive and impractical for mobile applications. Through optimisation of the simulation results the development of a realisable system with the best possible performance is possible.