CFAR processing with switching exponential smoothers for nonhomogeneous environments

Date

2012-05-01

Author

GURAKAN, Berk
Candan, Çağatay
Çiloğlu, Tolga

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

146
views

0
downloads

Conventional constant false alarm rate (CFAR) methods use a fixed number of cells to estimate the background variance. For homogeneous environments, it is desirable to increase the number of cells, at the cost of increased computation and memory requirements, in order to improve the estimation performance. For nonhomogeneous environments, it is desirable to use less number of cells in order to reduce the number of false alarms around the clutter edges. In this work, we present a solution with two exponential smoothers (first order IIR filters) having different time-constants to leverage the conflicting requirements of homogeneous and nonhomogeneous environments. The system is designed to use the filter having the large time-constant in homogeneous environments and to promptly switch to the filter having the small time constant once a clutter edge is encountered. The main advantages of proposed Switching IIR CFAR method are computational simplicity, small memory requirement (in comparison to windowing based methods) and its good performance in homogeneous environments (due to the large time-constant smoother) and rapid adaptation to clutter edges (due to the small time-constant smoother).

Subject Keywords

CFAR detection, Nonhomogeneous clutter, Exponential smoother

URI

https://hdl.handle.net/11511/46606

Journal

DIGITAL SIGNAL PROCESSING

DOI

https://doi.org/10.1016/j.dsp.2012.01.007

Collections

Department of Electrical and Electronics Engineering, Article

Suggestions

OpenMETU
Core

Cfar detection in k-distributed sea clutter Çetin, Ayşin; Hızal, Altunkan; Department of Electrical and Electronics Engineering (2008) Conventional fixed threshold detectors set a fixed threshold based on the overall statistical characteristics of the spatially uniform clutter over all ranges to give a specific probability of false alarm and detection. However, in radar applications clutter statistics are not known a priori. Constant False Alarm Rate (CFAR) techniques provide an adaptive threshold to estimate the clutter statistics and to distinguish targets from clutter. In Cell Averaging CFAR (CA-CFAR) the threshold is controlled by aver...
CFAR Processing with multiple exponential smoothers for nonhomogeneous environments Gürakan, Berk; Çiloğlu, Tolga; Candan, Çağatay; Department of Electrical and Electronics Engineering (2010) Conventional methods of CFAR detection always use windowing, in the sense that some number of cells are investigated and the target present/absent decision is made according to the composition of the cells in that window. The most commonly used versions of CFAR detection algorithms are cell averaging CFAR, smallest of cell averaging CFAR, greatest of cell averaging CFAR and order-statistics CFAR. These methods all use windowing to set the decision threshold. In this thesis, rather than using windowed CFAR a...
Ensemble adaptive tile prefetching using fuzzy logic Uluat, Mehmet Fatih; İşler, Veysi (2016-06-02) Prefetching is a process in which the necessary portion of data is predicted and loaded into memory beforehand. The increasing usage of geographic data in different types of applications has motivated the development of different prefetching techniques. Each prefetching technique serves a specific type of application, such as two-dimensional geographic information systems or three-dimensional visualization, and each one is crafted for the corresponding navigation patterns. However, as the boundary between t...
Robust pairwise multiple comparisons under short-tailed symmetric distributions Balci, Sibel; Akkaya, Ayşen (2015-11-02) In one-way ANOVA, most of the pairwise multiple comparison procedures depend on normality assumption of errors. In practice, errors have non-normal distributions so frequently. Therefore, it is very important to develop robust estimators of location and the associated variance under non-normality. In this paper, we consider the estimation of one-way ANOVA model parameters to make pairwise multiple comparisons under short-tailed symmetric (STS) distribution. The classical least squares method is neither effi...
ProFAB-open protein functional annotation benchmark Ozdilek, A. Samet; Atakan, Ahmet; Ozsari, Goekhan; Acar, Aybar; Atalay, Mustafa Ümit; DOĞAN, TUNCA; RİFAİOĞLU, AHMET SÜREYYA (2023-02-01) As the number of protein sequences increases in biological databases, computational methods are required to provide accurate functional annotation with high coverage. Although several machine learning methods have been proposed for this purpose, there are still two main issues: (i) construction of reliable positive and negative training and validation datasets, and (ii) fair evaluation of their performances based on predefined experimental settings. To address these issues, we have developed ProFAB: Open Pr...

Citation Formats

B. GURAKAN, Ç. Candan, and T. Çiloğlu, “CFAR processing with switching exponential smoothers for nonhomogeneous environments,” DIGITAL SIGNAL PROCESSING, pp. 407–416, 2012, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/46606.