Compressive Sensing Signal Detection Algorithm Based on Location Information of Sparse Coefficients
نویسندگان
چکیده
Without reconstructing the signal themselves, signal detection could be solved by detection algorithm, which directly processes sampling value obtained from compressive sensing signal. In current detection algorithm, as the judgment criterion, the threshold depends on Monte Carlo simulations, which takes too much time, affecting detection efficiency. Therefore, in this paper, we propose an algorithm to detect known signal in noise. First, get the sparse coefficients position information of to-be-detected signal in Transform domain. Then, acquire the position information of interested signal based on prior information. Finally, use the correlation of them as judgment criterion to complete detection. Simulation shows that under the same circumstances, compared with traditional algorithm, the algorithm this paper introduced can complete detection rapidly without reducing success rate.
منابع مشابه
Rice Classification and Quality Detection Based on Sparse Coding Technique
Classification of various rice types and determination of its quality is a major issue in the scientific and commercial fields associated with modern agriculture. In recent years, various image processing techniques are used to identify different types of agricultural products. There are also various color and texture-based features in order to achieve the desired results in this area. In this ...
متن کاملCompressive Sensing of Sparse Signals in the Hermite Transform Basis: Analysis and Algorithm for Signal Reconstruction
—An analysis of the influence of missing samples in signals exhibiting sparsity in the Hermite transform domain is provided. Based on the statistical properties derived for the Hermite coefficients of randomly undersampled signal, the probability of success in detection of signal components support is determined. Based on the probabilistic analysis, a threshold for the detection of signal compo...
متن کاملDirectional Remote Sensing
Concepts of directional remote sensing are put forward based on two-dimensional compressive sensing. Very little measured data are required to acquire and reconstruct change areas in directional remote sensing. The measured data in one-dimensional compressive sensing not only keep the energy of a sparse signal, but also inherit the sparse signal’s direction information. However, direction infor...
متن کاملComparison of threshold-based algorithms for sparse signal recovery
Intensively growing approach in signal processing and acquisition, the Compressive Sensing approach, allows sparse signals to be recovered from small number of randomly acquired signal coefficients. This paper analyses some of the commonly used threshold-based algorithms for sparse signal reconstruction. Signals satisfy the conditions required by the Compressive Sensing theory. The Orthogonal M...
متن کاملBlock-Based Compressive Sensing Using Soft Thresholding of Adaptive Transform Coefficients
Compressive sampling (CS) is a new technique for simultaneous sampling and compression of signals in which the sampling rate can be very small under certain conditions. Due to the limited number of samples, image reconstruction based on CS samples is a challenging task. Most of the existing CS image reconstruction methods have a high computational complexity as they are applied on the entire im...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- JDCTA
دوره 4 شماره
صفحات -
تاریخ انتشار 2010