A novel method of power spectrum estimation in CW radar signal processing

Author(s):  
Jiacheng Chen ◽  
Yilei Jiang ◽  
Weibo Xu ◽  
Shunlian Chai
2014 ◽  
Vol 926-930 ◽  
pp. 2857-2860 ◽  
Author(s):  
Bo Ni Su ◽  
Hong Xie ◽  
Xi Yao Hua

The spectrum estimation is a main content of modern signal processing, it is very important for random signal detection and analysis. This paper researched the classical spectrum estimation method, simulated the periodogram method, Barlett method, and Welch method of power spectrum estimation, then mainly discussed the spectral resolution about different length of data, also discussed the resolution of the spectral estimation and the performance of variance in the different way.


Author(s):  
Kalfika Yani ◽  
Fiky Y Suratman ◽  
Koredianto Usman

The radar air surveillance system consists of 4 main parts, there are antenna, RF front-end, radar signal processing, and radar data processing. Radar signal processing starts from the baseband to IF section. The radar waveform consists of two types of signal, there are continuous wave (CW) radar, and pulse compression radar [1]. Range resolution for a given radar can be significantly improved by using very short pulses. Pulse compression allows us to achieve the average transmitted power of a relatively long pulse, while obtaining the range resolution corresponding to a short pulse. Pulse compression have compression gain. With the same power, pulse compression radar can transmit signal further than CW radar. In the modern radar, waveform is implemented in digital platform. With digital platform, the radar waveform can optimize without develop the new hardware platform. Field Programmable Gate Array (FPGA) is the best platform to implemented radar signal processing, because FPGA have ability to work in high speed data rate and parallel processing. In this research, we design radar signal processing from baseband to IF using Xilinx ML-605 Virtex-6 platform which combined with FMC-150 high speed ADC/DAC.


2021 ◽  
Author(s):  
Hajar Abedi ◽  
Clara Magnier ◽  
Vishvam Mazumdar ◽  
George Shaker

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