This chapter illustrates innovative signal processing techniques and architectures for radar systems based on the exploitation of opportunistic communication signals, namely WiFi and DVB-T OFDM signals. It covers three different applications and operational scenarios where these systems can be effectively employed for surveillance purposes, namely (i) short range monitoring based on WLAN transmissions, (ii) radar systems on board of moving platforms, and (iii) low-cost forward scatter radar sensors for distributed surveillance of designed areas. In all cases, the peculiar characteristics of the considered application are discussed, and ad hoc solutions are proposed. While the proposed approaches can be exploited in both active and passive radar systems, the discussion is supported by experimental results obtained using passive radar prototypes either developed at Sapienza University of Rome or by research partners. This gives the opportunity to understand the benefits of these approaches in real world scenarios and to demonstrate their effectiveness against experimental datasets.
OFDM Radar Based on Communications Signals of Opportunity
Bongioanni, Carlo;
2024-01-01
Abstract
This chapter illustrates innovative signal processing techniques and architectures for radar systems based on the exploitation of opportunistic communication signals, namely WiFi and DVB-T OFDM signals. It covers three different applications and operational scenarios where these systems can be effectively employed for surveillance purposes, namely (i) short range monitoring based on WLAN transmissions, (ii) radar systems on board of moving platforms, and (iii) low-cost forward scatter radar sensors for distributed surveillance of designed areas. In all cases, the peculiar characteristics of the considered application are discussed, and ad hoc solutions are proposed. While the proposed approaches can be exploited in both active and passive radar systems, the discussion is supported by experimental results obtained using passive radar prototypes either developed at Sapienza University of Rome or by research partners. This gives the opportunity to understand the benefits of these approaches in real world scenarios and to demonstrate their effectiveness against experimental datasets.| File | Dimensione | Formato | |
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