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Paper Information

Journal:   JOURNAL OF RADAR   FALL 2014 , Volume 2 , Number 3 (SERIAL NO. 5); Page(s) 1 To 11.
 
Paper: 

ADAPTIVE RADAR SIGNAL DETECTION IN GAUSSIAN CLUTTER WITH AUTOREGRESSIVE MODEL USING KALMAN FILLTER

 
 
Author(s):  TABAN M.R.*, SHEIKH MOZAFFARI A.
 
* YAZD UNIVERSITY
 
Abstract: 
In this paper, we deal with the problem of adaptive coherent signal detection in Gaussian interference (clutter plus noise) for surveillance pulse radars. Some of the adaptive radar detectors exploit the AR model for clutter. Most of these detectors have been obtained using the GLR test. This test relies on the maximum likelihood estimation whose accuracy depends on the number of data. Whereas, the length of data is not too long in practical applications, and because of the recursive nature of AR model, in this paper we suggest two methods for estimating the clutter parameters using the Kalman filter based on the initial and secondary data respectively. According to these methods, we propose two adaptive detectors called ARKD and ARKSD. Our investigations show that the proposed Kalman filter-based detectors improve the detection performance especially in low number data.
 
Keyword(s): ADAPTIVE DETECTION, AUTOREGRESSIVE CLUTTER, KALMAN FILTER
 
 
References: 
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Citations: 
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+ Click to Cite.
APA: Copy

TABAN, M., & SHEIKH MOZAFFARI, A. (2014). ADAPTIVE RADAR SIGNAL DETECTION IN GAUSSIAN CLUTTER WITH AUTOREGRESSIVE MODEL USING KALMAN FILLTER. JOURNAL OF RADAR, 2(3 (SERIAL NO. 5)), 1-11. https://www.sid.ir/en/journal/ViewPaper.aspx?id=419260



Vancouver: Copy

TABAN M.R., SHEIKH MOZAFFARI A.. ADAPTIVE RADAR SIGNAL DETECTION IN GAUSSIAN CLUTTER WITH AUTOREGRESSIVE MODEL USING KALMAN FILLTER. JOURNAL OF RADAR. 2014 [cited 2021December02];2(3 (SERIAL NO. 5)):1-11. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=419260



IEEE: Copy

TABAN, M., SHEIKH MOZAFFARI, A., 2014. ADAPTIVE RADAR SIGNAL DETECTION IN GAUSSIAN CLUTTER WITH AUTOREGRESSIVE MODEL USING KALMAN FILLTER. JOURNAL OF RADAR, [online] 2(3 (SERIAL NO. 5)), pp.1-11. Available: https://www.sid.ir/en/journal/ViewPaper.aspx?id=419260.



 
 
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