As a modern radar receiver must rapidly search a large frequency range with maximum sensitivity, capabilities such as high instantaneous dynamic range (IDR), good multiple-signal-detection capability, wider bandwidth (BW), and high-frequency resolution are indispensable. Many techniques proposed to improve digital wideband receiver performance are computationally intensive and limit their real-time performance due to hardware constraint. In this paper, an innovative three gigasample-per-second hybrid computing platform digital wideband receiver system is presented, which employs two Nvidia Tesla C2050 graphics processor units and a Xilinx Virtex-5 field-programmable gate array for hardware acceleration to drastically improve receiver performance over its predecessor designs. The receiver detects five simultaneous signals in 1.25-GHz BW (125-1375 MHz) with a maximum IDR of 42.5 dB and a frequency resolution of 0.5 MHz. The proposed receiver architecture achieves high-resolution spectral estimation and employs a hardware mechanism for multiple-signal detection before the next set of data arrives for processing.<\/p>\n","protected":false},"excerpt":{"rendered":"
As a modern radar receiver must rapidly search a large frequency range with maximum sensitivity, capabilities such as high instantaneous dynamic range (IDR), good multiple-signal-detection capability, wider bandwidth (BW), and high-frequency resolution are indispensable. Many techniques proposed to improve digital wideband receiver performance are computationally intensive and limit their real-time performance due to hardware constraint. […]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[3,41],"tags":[377,20,67,1789,378],"class_list":["post-4507","post","type-post","status-publish","format-standard","hentry","category-paper","category-signal-processing","tag-fpga","tag-nvidia","tag-performance","tag-signal-processing","tag-tesla-c2050"],"views":2219,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4507","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=4507"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4507\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4507"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4507"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4507"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}