Browsing by Author "Vaccarono, Mattia, author"
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Item EmbargoCoexistence of weather radars and communication systems: model to identify interfering sources and mitigation solutions(Colorado State University. Libraries, 2023) Vaccarono, Mattia, author; Chandrasekaran, Chandra V., advisor; Cheney, Margaret, committee member; Jayasumana, Anura, committee member; Popat, Ketul, committee memberElectromagnetic spectrum is a finite resource. Weather radars are one of the many sources which use electromagnetic waves. The availability of spectrum bands that can be assigned to a specific user is limited. Consequently, the electromagnetic spectrum is shared by different application in the same frequency band. This is the specific case of C-band weather radars, which operate in the 5.6GHz band, sharing the same frequencies with Radio Local Area Networks, Wireless Local Area Networks and HiperLAN systems. These telecommunication systems are continuously increasing in rural areas as broadband Internet access points. The coexistence of C-band weather radar and such systems is nowadays a primary topic in the weather radar community. The amount of interference received by weather radars are affecting the data quality, especially for polarimetric observations. Electromagnetic interference may also appear at higher frequencies, such as the X-band located around 9.3GHz. These frequencies are used by weather radars for hydrological purposes. The dense radar network deployed in Dallas Fort Worth area and the mobile radar managed by Arpa Piemonte operate at X-band and they receive interfering signals. These signals have been detected during a field measurement campaign using both the mobile weather radar and a vector signal analyzer able to perform real time analysis. A technique to identify the likely interfering sources is discussed, which can be used by the National Regulatory Authorities or Regional Agencies, such as the Physics and Industrial Risk Department of Arpa Piemonte, Italy, in charge of the telecommunication authorization processes. The model may be applied to a telecommunication tower transmitting at the same frequency of a given radar and in case of likely interference, mitigation strategies could be set during the tower installation, i.e. changing the antenna direction or tilt. Over the years, many RFI removal and mitigation tools have been discussed in the literature, but only few are currently implemented on operational weather radars. This work, instead, aims to implement mitigation solutions that can be implemented by National Weather Services. The electromagnetic interference may be removed at different levels: from the received signals to the processed radar products, such as reflectivity maps that are shown to general public. In order to make possible the interference removal also to those National Weather Services, or radar management services, which are not able to act on the radar signal processor to implement deeper mitigation tools, a RFI mitigation solution based on image processing is shown. This method does not require to access the radar signal processor, but it does not mitigate the effect of interference overlapped with weather echoes. Then, based on the interfering signals features, a mitigation solution has been developed. The interfering signals are removed before received signals are processed to obtain radar moments. The proposed method has been tested with good performances in clear air echoes at both C and X-bands. A study case has been selected to evaluate its performances during precipitation events. The proposed mitigation solution is applied to the received signals to remove interfering signals and to reconstruct the residual information. The radar reflectivity is computed and it is compared to the operational radar Z product. A Swiss C-band radar is selected as reference to validate the mitigation solution. The interfering signals are properly removed and the missing data in the received radar pulses are computed by smoothing from adjacent range gates and pulses. Actually, removing only the interfering signals the proposed solution is able to preserve the meteorological echoes which lead to a better estimate of the reflectivity values, especially in case of weak echoes (i.e. light rain or drizzle). The Interference to Signal Ratio (ISR) is considered the metric to quantitatively evaluate the mitigation performance as ISR difference between processed and received signals. The proposed mitigation solution can achieve up to 20dB suppression.