The influence of random element displacement on DOA estimates obtained with (Khatri-Rao-)root-MUSIC

Although a wide range of direction of arrival (DOA) estimation algorithms has been described for a diverse range of array configurations, no specific stochastic analysis framework has been established to assess the probability density function of the error on DOA estimates due to random errors in the array geometry. Therefore, we propose a stochastic collocation method that relies on a generalized polynomial chaos expansion to connect the statistical distribution of random position errors to the resulting distribution of the DOA estimates. We apply this technique to the conventional root-MUSIC and the Khatri-Rao-root-MUSIC methods. According to Monte-Carlo simulations, this novel approach yields a speedup by a factor of more than 100 in terms of CPU-time for a one-dimensional case and by a factor of 56 for a two-dimensional case

A Search for Cosmic Microwave Background Anisotropies on Arcminute Scales with Bolocam

We have surveyed two science fields totaling one square degree with Bolocam at 2.1 mm to search for secondary CMB anisotropies caused by the Sunyaev- Zel'dovich effect (SZE). The fields are in the Lynx and Subaru/XMM SDS1 fields. Our survey is sensitive to angular scales with an effective angular multipole of l_eff = 5700 with FWHM_l = 2800 and has an angular resolution of 60 arcseconds FWHM. Our data provide no evidence for anisotropy. We are able to constrain the level of total astronomical anisotropy, modeled as a flat bandpower in C_l, with frequentist 68%, 90%, and 95% CL upper limits of 590, 760, and 830 uKCMB^2. We statistically subtract the known contribution from primary CMB anisotropy, including cosmic variance, to obtain constraints on the SZE anisotropy contribution. Now including flux calibration uncertainty, our frequentist 68%, 90% and 95% CL upper limits on a flat bandpower in C_l are 690, 960, and 1000 uKCMB^2. When we instead employ the analytic spectrum suggested by Komatsu and Seljak (2002), and account for the non-Gaussianity of the SZE anisotropy signal, we obtain upper limits on the average amplitude of their spectrum weighted by our transfer function of 790, 1060, and 1080 uKCMB^2. We obtain a 90% CL upper limit on sigma8, which normalizes the power spectrum of density fluctuations, of 1.57. These are the first constraints on anisotropy and sigma8 from survey data at these angular scales at frequencies near 150 GHz.Comment: 68 pages, 17 figures, 2 tables, accepted for publication in Ap

On the performance of minimum redundancy array for multisource direction finding

As an application of power spectrum estimation, the multi-source direction finding has been evolved from conventional FFT method to Superresolution methods such as Multiple Signal Classification(MUSIC) algorithm. Uniform Regular Array(URA) was mainly used in all these approaches. The Minimum Redundancy array(MRA); a non-uniform thinned array which results in an input signals covariance matrix with minimum redundancy has been shown to have certain interesting properties for spectrum estimation. Only recently it was suggested to use the MRA for spatial estimation. The purpose of this research was to study the performance of this array in multi-source direction finding estimation and compare it to the result obtained with URA. Although the emphasis in this research is on using the popular MUSIC algorithm, other algorithms are also considered. Among the topics related to the MRA performance studied in the course of this research are 1. Effect of random displacement of the array element location on the performance of multi-source direction finding. 2. Performance of the MRA versus the URA using MUSIC and Minimum-Norm algorithms. 3. Performance of the MUSIC based direction finding using different covariance matrix estimates for URA and MRA. 4. The error probability of estimating the number (two in particular) of closely located sources with MRA versus URA