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The Global Positioning System (GPS) is a satellite based navigation system. GPS satellites transmit signals that allow one to determine the location of GPS receivers. In GPS, a typical technique for kinematic position estimation is differential positioning where two receivers are used: one receiver is stationary and its exact position is known, and the(More)
This paper gives componentwise perturbation analyses for Q and R in the QR factorization A = QR, Q T Q = I, R upper triangular, for a given real m × n matrix A of rank n. Such specific analyses are important for example when the columns of A are badly scaled. First order perturbation bounds are given for both Q and R. The analyses more accurately reflect(More)
A wavelet approach is presented for estimating a partially linear model (PLM). We ÿnd an estimator of the PLM by minimizing the square of the l2 norm of the residual vector while penalizing the l1 norm of the wavelet coeecients of the nonparametric component. This approach, an extension of the wavelet approach for nonparametric regression problems, avoids(More)
An efficient regularization approach is proposed for decoding underdetermined multiple input multiple output (MIMO) systems. The main idea is to transform an underdetermined integer least squares problem to an equivalent overdetermined integer least squares problem by using part of the transmit vector to do a regularization. Some strategies are proposed to(More)
— A box-constrained integer least squares problem (BILS) arises from several wireless communications applications. Solving a BILS problem usually has two stages: reduction (or preprocessing) and search. This paper presents a reduction algorithm and a search algorithm. Unlike the typical reduction algorithms , which use only the information of the lattice(More)
We explain an interesting property of minimum residual iterative methods for the solution of the linear least squares (LS) problem. Our analysis demonstrates that the stopping criteria commonly used with these methods can in some situations be too conservative, causing any chosen method to perform too many iterations or even fail to detect that an(More)
—A common method to estimate an unknown integer parameter vector in a linear model is to solve an integer least squares (ILS) problem. A typical approach to solving an ILS problem is sphere decoding. To make a sphere decoder faster, the well-known LLL reduction is often used as preprocessing. The Babai point produced by the Babai nearest plane algorithm is(More)
In GNSS, for fixing integer ambiguities and estimating positions, a mixed integer least squares problem has to be solved. The MATLAB package MILES provides fast and numerically reliable routines to solve this problem. In the process of solving a mixed integer least squares problem, an ordinary integer least squares problem is solved. Thus this package can(More)
A new method is proposed to solve an ellipsoid-constrained integer least squares (EILS) problem arising in communications. In this method, the LLL reduction, which is cast as a QRZ factorization of a matrix, is used to transform the original EILS problem to a reduced EILS problem, and then a search algorithm is proposed to solve the reduced EILS problem.(More)
In 1982, Arjen Lenstra, Hendrik Lenstra Jr. and László Lovász introduced an efficiently computable notion of reduction of basis of a Euclidean lattice that is now commonly referred to as LLL-reduction. The precise definition involves the R-factor of the QR factorization of the basis matrix. In order to circumvent the use of rational/exact arithmetic with(More)