Enhanced Direction of Arrival Estimation through Electromagnetic Modeling

Engineering is a high art that balances modeling the physical world and designing meaningful solutions based on those models. Array signal processing is no exception, and many innovative and creative solutions have come from the field of array processing. However, many of the innovative algorithms that permeate the field are based on a very simple signal model of an array. This simple, although powerful, model is at times a pale reflection of the complexities inherent in the physical world, and this model mismatch opens the door to the performance degradation of any solution for which the model underpins. This dissertation seeks to explore the impact of model mismatch upon common array processing algorithms. To that end, this dissertation brings together the disparate topics of electromagnetics and signal processing. Electromagnetics brings a singular focus on the physical interactions of electromagnetic waves and physical array structures, while signal processing brings modern computational power to solve difficult problems. We delve into model mismatch in two ways; first, by developing a blind array calibration routine that estimates model mismatch and incorporates that knowledge into the reiterative superresoluiton (RISR) direction of arrival estimation algorithm; second, by examining model mismatch between a transmitting and receiving array, and assessing the impact of this mismatch on prolific direction of arrival estimation algorithms. In both of these studies we show that engineers have traded algorithm performance for model simplicity, and that if we are willing to deal with the added complexity we can recapture that lost performance

A subspace-based method for DOA estimation of uniform linear array in the presence of mutual coupling

This paper develops a subspace-based method for direction-of-arrival (DOA) estimation of uniform linear array (ULA) in the presence of mutual coupling. As the mutual coupling coefficient between two sensor elements is inversely related to their separation and is negligible when they are separated by a few wavelengths, the mutual coupling matrix (MCM) of a ULA can be well approximated as a banded symmetric Toeplitz matrix, which greatly reduces the number of unknown parameters to be estimated. Using the subspace principle, we propose a new method for joint estimation of the DOAs of incoming signals and banded symmetric Toeplitz MCM by reconstructing the steering vector to a specific matrix form. The proposed method achieves a better performance especially for weak signals than the method in [8], since the whole array, instead of the middle subarray in [8], is used for DOA estimation. Simulation results illustrate that both DOAs and mutual coupling coefficients can be estimated efficiently with the proposed method. ©2010 IEEE.published_or_final_versionThe IEEE International Symposium on Circuits and Systems (ISCAS) 2010, Paris, France, 30 May-2 June 2010. In Proceedings of ISCAS, 2010, p. 1879-188

Adaptive Antenna Arrays for Ad-Hoc Millimetre-Wave Wireless Communications

New technologies that employ millimetre-wave frequency bands to achieve high speed wireless links are gaining more attention (Dyadyuk et. al., 2007, 2009b, 2010a; Hirata et. al., 2006; Lockie & Peck, 2009; Kasugi et. al., 2009; Wells, 2009) due to increasing demand for wideband wireless communications. Very wide uncongested spectrum is available in the E—bands (71-76 GHz and 81-86 GHz) recently allocated for wireless communications in USA, Europe, Korea, Russia and Australia. The E-band provides an opportunity for line-of – sight (LOS) links with higher data rates, well suited for fibre replacement and backhaul applications. Future mobile and ad-hoc communications networks will require higher bandwidth and longer range. An ad-hoc or mobile (e.g. inter-aircraft) network that relies on high gain antennas also requires beam scanning. Adaptive antenna arrays have found a wide rage of applications and are becoming essential parts of wireless communications systems (Abbaspour-Tamijani & Sarabandi, 2003; Do-Hong & Russer, 2004; Gross, 2005; Guo, 2004; Krim & Viberg, 1996; Mailloux, 2005, 2007; Rogstad et al., 2003; Singh et al., 2008). While the spectrum available in the millimetre-wave frequency bands enables multi-gigabit-per second data rates, the practically achievable communication range is limited by several factors. These include the higher atmospheric attenuation at these frequencies and limited output power of monolithic microwave integrated circuits (MMIC) (Doan et al., 2004; Dyadyuk et al., 2008a; Kasper et al., 2009; Floyd et al., 2007; Reynolds et. al., 2006; Vamsi et. al., 2005, Zirath et al., 2004) due to physical constraints. Therefore, the performance of the ad-hoc or mobile millimetre-wave networks requires enhancement by using spatial power combining antenna arrays

Algorithms and Circuits for Analog-Digital Hybrid Multibeam Arrays

Fifth generation (5G) and beyond wireless communication systems will rely heavily on larger antenna arrays combined with beamforming to mitigate the high free-space path-loss that prevails in millimeter-wave (mmW) and above frequencies. Sharp beams that can support wide bandwidths are desired both at the transmitter and the receiver to leverage the glut of bandwidth available at these frequency bands. Further, multiple simultaneous sharp beams are imperative for such systems to exploit mmW/sub-THz wireless channels using multiple reflected paths simultaneously. Therefore, multibeam antenna arrays that can support wider bandwidths are a key enabler for 5G and beyond systems. In general, N-beam systems using N-element antenna arrays will involve circuit complexities of the order of N2. This dissertation investigates new analog, digital and hybrid low complexity multibeam beamforming algorithms and circuits for reducing the associated high size, weight, and power (SWaP) complexities in larger multibeam arrays. The research efforts on the digital beamforming aspect propose the use of a new class of discrete Fourier transform (DFT) approximations for multibeam generation to eliminate the need for digital multipliers in the beamforming circuitry. For this, 8-, 16- and 32-beam multiplierless multibeam algorithms have been proposed for uniform linear array applications. A 2.4 GHz 16-element array receiver setup and a 5.8 GHz 32-element array receiver system which use field programmable gate arrays (FPGAs) as digital backend have been built for real-time experimental verification of the digital multiplierless algorithms. The multiplierless algorithms have been experimentally verified by digitally measuring beams. It has been shown that the measured beams from the multiplierless algorithms are in good agreement with the exact counterpart algorithms. Analog realizations of the proposed approximate DFT transforms have also been investigated leading to low-complex, high bandwidth circuits in CMOS. Further, a novel approach for reducing the circuit complexity of analog true-time delay (TTD) N-beam beamforming networks using N-element arrays has been proposed for wideband squint-free operation. A sparse factorization of the N-beam delay Vandermonde beamforming matrix is used to reduce the total amount of TTD elements that are needed for obtaining N number of beams in a wideband array. The method has been verified using measured responses of CMOS all-pass filters (APFs). The wideband squint-free multibeam algorithm is also used to propose a new low-complexity hybrid beamforming architecture targeting future 5G mmW systems. Apart from that, the dissertation also explores multibeam beamforming architectures for uniform circular arrays (UCAs). An algorithm having N log N circuit complexity for simultaneous generation of N-beams in an N-element UCA is explored and verified

A New Restriction on Low-Redundancy Restricted Array and Its Good Solutions

In array signal processing, a fundamental problem is to design a sensor array with low-redundancy and reduced mutual coupling, which are the main features to improve the performance of direction-of-arrival (DOA) estimation. For a $N$-sensor array with aperture $L$, it is called low-redundancy (LR) if the ratio $R=N(N-1)/(2L)$ is approaching the Leech's bound $1.217\leq R_{opt}\leq 1.674$ for $N\rightarrow\infty$; and the mutual coupling is often reduced by decreasing the numbers of sensor pairs with the first three smallest inter-spacings, denoted as $\omega(a)$ with $a\in\{1,2,3\}$. Many works have been done to construct large LRAs, whose spacing structures all coincide with a common pattern ${\mathbb D}=\{a_1,a_2,\ldots,a_{s_1},c^\ell,b_1,b_2,\ldots,b_{s_2}\}$ with the restriction $s_1+s_2=c-1$. Here $a_i,b_j,c$ denote the spacing between adjacent sensors, and $c$ is the largest one. The objective of this paper is to find some new arrays with lower redundancy ratio or lower mutual coupling compared with known arrays. In order to do this, we give a new restriction for ${\mathbb D}$ to be $s_1+s_2=c$ , and obtain 2 classes of $(4r+3)$-type arrays, 2 classes of $(4r+1)$-type arrays, and 1 class of $(4r)$-type arrays for any $N\geq18$. Here the $(4r+i)$-Type means that $c\equiv i\pmod4$. Notably, compared with known arrays with the same type, one of our new $(4r+1)$-type array and the new $(4r)$-type array all achieves the lowest mutual coupling, and their uDOFs are at most 4 less for any $N\geq18$; compared with SNA and MISC arrays, the new $(4r)$-type array has a significant reduction in both redundancy ratio and mutual coupling. We should emphasize that the new $(4r)$-type array in this paper is the first class of arrays achieving $R<1.5$ and $\omega(1)=1$ for any $N\geq18$

Subspace methods for self-calibration of ULAs with unknown mutual coupling: A false-peak analysis

Self-calibration can mitigate the adverse effect of array imperfections in direction-of-arrival (DoA) estimation. In this paper, we consider self-calibration of uniform linear arrays (ULAs) with unknown mutual coupling and focus on subspace-based methods. By modeling the effect of mutual coupling through complex symmetric Toeplitz matrices, we first analyze its influence to existing subspace methods. Our analytical results illustrate that mutual coupling can induce false peaks in spatial spectra of these methods, and more importantly, most of these peaks are predictable. Based on the analytical results, we then propose new spectra to suppress these predictable false peaks, and new self-calibration algorithms for the proposed spectra. Simulations are performed to validate our analytical results and to illustrate the advantages of the proposed algorithms