Multi-Step Knowledge-Aided Iterative ESPRIT for Direction Finding

In this work, we propose a subspace-based algorithm for DOA estimation which iteratively reduces the disturbance factors of the estimated data covariance matrix and incorporates prior knowledge which is gradually obtained on line. An analysis of the MSE of the reshaped data covariance matrix is carried out along with comparisons between computational complexities of the proposed and existing algorithms. Simulations focusing on closely-spaced sources, where they are uncorrelated and correlated, illustrate the improvements achieved.Comment: 7 figures. arXiv admin note: text overlap with arXiv:1703.1052

Randomized Rank-Revealing QLP for Low-Rank Matrix Decomposition

The pivoted QLP decomposition is computed through two consecutive pivoted QR decompositions, and provides an approximation to the singular value decomposition. This work is concerned with a partial QLP decomposition of low-rank matrices computed through randomization, termed Randomized Unpivoted QLP (RU-QLP). Like pivoted QLP, RU-QLP is rank-revealing and yet it utilizes random column sampling and the unpivoted QR decomposition. The latter modifications allow RU-QLP to be highly parallelizable on modern computational platforms. We provide an analysis for RU-QLP, deriving bounds in spectral and Frobenius norms on: i) the rank-revealing property; ii) principal angles between approximate subspaces and exact singular subspaces and vectors; and iii) low-rank approximation errors. Effectiveness of the bounds is illustrated through numerical tests. We further use a modern, multicore machine equipped with a GPU to demonstrate the efficiency of RU-QLP. Our results show that compared to the randomized SVD, RU-QLP achieves a speedup of up to 7.1 times on the CPU and up to 2.3 times with the GPU

Issues Around Researching OHS of Samoan Migrant Workers

Workers from Pacific nations constitute a substantial proportion of the labour force in NZ, particularly in Auckland, which has one of the largest concentrations of Pacific Island workers in the world. Samoans constitute the largest Pacific ethnic group in NZ, comprising 131,103 or 49% of the resident Pacific population (265,974) (Statistics NZ, 2010). However, Pacific Island workers in NZ are typically employed in low paid, precarious, hazardous work that often has little chance of advancement. There is also some evidence that Pacific Island workers are over­represented in NZ’s work­related injury and illness statistics (Allen & Clarke, 2006). While occupational health and safety (OHS) of Pacific Island migrant workers highlights a number of issues, studies often provide inadequate explanations of what exactly is occurring or fully capture the working experiences of Pacific Island migrant workers. This paper reports on the initial work undertaken as part of an international collaborative study located in Samoa and NZ, aimed at investigating the OHS experiences of Samoan migrant workers. In particular, the paper presents a multi­layered framework and a set of research principles that can be used to illuminate often inaccessible populations located in changing working and living environments. Finally, this study exemplifies the complex issues surrounding the migrant workers’ health and safety, workers’ compensation and rehabilitation