Method for Generating Noise Radar Signals

2017 ◽  
Author(s):  
A. Yildirim ◽  
M. Ispir ◽  
O. Ozdil
Keyword(s):  
Noise Radar ◽  
Radar Signals

Noise Radar Technology

2001 ◽  
Vol 55 (12) ◽  
pp. 9 ◽  
Author(s):  
K. A. Lukin
Keyword(s):  
Noise Radar

MODELING REFLECTED RADAR SIGNALS FOR MULTI-CHANNEL EARTH REMOTE SENSING SYSTEM

2020 ◽  
Author(s):  
Yu. V. Markov ◽  
◽  
A. S. Bokov ◽  
V. G. Vazhenin ◽  
V. V. Mukhin ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Earth Remote Sensing ◽  
Sensing System ◽  
Radar Signals

scholarly journals Estimating the Instantaneous Frequency of Linear and Nonlinear Frequency Modulated Radar Signals—A Comparative Study

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2840
Author(s):  
Hubert Milczarek ◽  
Czesław Leśnik ◽  
Igor Djurović ◽  
Adam Kawalec
Keyword(s):  
Instantaneous Frequency ◽  
Early Warning Systems ◽  
Vital Role ◽  
Estimation Methods ◽  
Radar Signal ◽  
Nonlinear Frequency ◽  
Modulation Recognition ◽  
Electronic Warfare ◽  
Time Frequency ◽  
Radar Signals

Automatic modulation recognition plays a vital role in electronic warfare. Modern electronic intelligence and electronic support measures systems are able to automatically distinguish the modulation type of an intercepted radar signal by means of real-time intra-pulse analysis. This extra information can facilitate deinterleaving process as well as be utilized in early warning systems or give better insight into the performance of hostile radars. Existing modulation recognition algorithms usually extract signal features from one of the rudimentary waveform characteristics, namely instantaneous frequency (IF). Currently, there are a small number of studies concerning IF estimation methods, specifically for radar signals, whereas estimator accuracy may adversely affect the performance of the whole classification process. In this paper, five popular methods of evaluating the IF–law of frequency modulated radar signals are compared. The considered algorithms incorporate the two most prevalent estimation techniques, i.e., phase finite differences and time-frequency representations. The novel approach based on the generalized quasi-maximum likelihood (QML) method is also proposed. The results of simulation experiments show that the proposed QML estimator is significantly more accurate than the other considered techniques. Furthermore, for the first time in the publicly available literature, multipath influence on IF estimates has been investigated.

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