Abstract
In this paper, target detection is studied for a cloud multiple-input multiple-output (MIMO) radar system, where each receiver communicates with a fusion center (FC) through a backhaul network. To reduce communication burden, local measurements at each receiver are quantized before they are sent to the FC. Under a bitrate constraint for each local sensor, we derive the detection probability of the cloud radar and analyze effects of the sampling rate and bits per sample on the detection performance. The quantizer output is initially modeled using direct analysis (DA), and then the Gaussian quantization error approximation (GQEA) method is employed to facilitate theoretical analysis. We verify that these two methods lead to close enough detection performance for large enough number of bits per sample. The tradeoff between the sampling rate and bits per sample is presented analytically and numerically.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
