Title :
Almost sure identifiability of constant modulus multidimensional harmonic retrieval
Author :
Xiangqian Liu ; Sidiropoulos, Nicholas
Author_Institution :
Dept. of Electr. & Comput. Eng., Minnesota Univ., Minneapolis, MN
fDate :
9/1/2002 12:00:00 AM
Abstract :
In a previous paper by Jiang et al. (see ibid. vol.49, p.1849-59, 2001) it has been shown that up to └K/2┘ ┌L/2┐ two-dimensional (2-D) exponentials are almost surely identifiable from a K×L mixture, assuming regular sampling at or above Nyquist in both dimensions. This holds for damped or undamped exponentials. As a complement, in this article, we show that up to ┌K/2┐ ┌L/2┐ undamped exponentials can be uniquely recovered almost surely. Multidimensional conjugate folding is used to achieve this improvement. The main result is then generalized to N>2 dimensions. The gain is interesting from a theoretical standpoint but also for small 2-D sensor arrays or higher dimensions and odd sample sizes.
Keywords :
array signal processing; harmonic analysis; identification; multidimensional signal processing; signal sampling; 2D exponentials; 2D sensor arrays; Nyquist sampling; almost sure identifiability; array signal processing; constant modulus multidimensional harmonic retrieval; damped exponentials; harmonic analysis; multidimensional conjugate folding; multidimensional signal processing; regular sampling; sample size; two-dimensional exponentials; undamped exponentials; Array signal processing; Frequency estimation; Harmonic analysis; Multidimensional signal processing; Multidimensional systems; Radar signal processing; Sampling methods; Sensor arrays; Spectral analysis; Two dimensional displays;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2002.801933