Software-Defined Radar System for Landslides Monitoring Sandra Costanzo1, Giuseppe Di Massa1, Antonio Costanzo1, Antonio Borgia1 , Antonio Raffo1 , Giuseppe Viggiani1 and Pasquale Versace1 1
DIMES – University of Calabria 87036 Rende (CS), Italy
[email protected]
Abstract. An integrated system for landslides early warning, based on a flexible network architecture and including different sensors, is described to monitoring landslides evolution in critical scenarios. Particular focus is devoted on the experimental assessment of an L-band Software Defined Radar sensor, specifically designed for the application, by discussing the measurement results obtained on a real landslide scenario located on the A3 highway in Calabria (Italy). In particular, a mathematical estimator useful for the proper detection of landslide movements is defined and applied to the measured range profiles, thus demonstrating the usefulness of the proposed radar monitoring approach.
Keywords: Software Defined Radar, Landslides Early Warning.
1 Introduction A landslide is a complex geological phenomenon involving a wide range of possible ground movements, such as rock-falls, deep failure of slopes, and shallow debris flows. Due to the large set of physical parameters involved in the phenomenon, landslides monitoring is a complex operation, which requires expertise in various different fields [1]. In recent years, early warning systems are becoming increasingly important for the landslide monitoring, due to their effectiveness in the reduction of risk, with the adoption of low-cost equipment when compared to traditional engineered mitigation tools [2]. As a matter of fact, the reduction of the total cost, both in terms of employed devices as well as in terms of management, is one of the main goal for the design of early warning systems, especially in those areas where financial resources are not so adequate to face the problem with a complex structural approach. In order to maintain a good scalability, a distributed sensor measurement system, with the possibility to integrate different devices located in different points of the monitored scenario, should be arranged. In this way, several typology of heterogeneous sensors may be used for obtaining a precise description of the scenario under analysis and a realistic evaluation of the landslide risk. All data should be Ó Springer International Publishing Switzerland 2016 Á. Rocha et al. (eds.), New Advances in Information Systems and Technologies, Advances in Intelligent Systems and Computing 445, DOI 10.1007/978-3-319-31307-8_34
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collected and analyzed into a control center using a flexible network for the communication with devices. Using low-cost radar systems, developed with a Software Defined Radar (SDRadar) approach [3-5], significantly decreases the total cost of the system and leads to a fast and practical monitoring activity. In the framework of a national project on “Landslides Early Warning” , a Software Defined Radar, a radar scatterometer, and other different devices are integrated into the same system in order to monitoring real landslide scenarios [6]. In this work, the final architecture of the whole system is fully described. Furthermore, the experimental assessment of the realized L-band SDRadar on a real scenario is discussed to show the ability to retrieve real-time landslide movements. The paper is organized as follows: the system architecture is described in Section2, while the experimental results obtained on the A3 highway in Calabria (Italy) are reported in Section 3. Finally, conclusions are outlined in Section 4.
2 System Architecture An integrated system for “Landslide Monitoring, Early Warning and Risk Mitigation along Lifelines”, with acronym LEWIS, is a project inserted in the framework of the National Operational Programme 2007-13 “Research and Competitiveness”, cofunded by the European Regional Development Fund, and funded by the Ministry of Research (MIUR) [6]. The system includes many heterogeneous components related each other and allows many different operations. Standard criteria for the evaluation and mapping of landslides susceptibility are adopted, and different sensors are placed and linked to a center for data acquisition and processing through a telecommunication network with an ad-hoc multithread based architecture. The main operations of the system are reported in Fig. 1.
Fig. 1. Different operations of Lewis System
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For a direct evaluation of the parameters characterizing the scenario, a set of punctual monitoring devices are placed directly on the landslide front. Areal monitoring devices, namely an X-band scatterometer and the L-band SDRadar, are also integrated in order to completely cover the scenario. After a local pre-processing, measured data are transmitted through a transmission network to a data collecting and processing center, where they are stored in real time and further elaborated. The transmission network is developed in order to interface heterogeneous data, using an ad hoc transmission protocol and a flexible middleware ready for future expanding of the system to include other typologies of sensors. A set of mathematical models are considered to evaluate landslide movements and eventually transmit a warning to a control and mitigation center, where operative decisions are taken on the basis of the warning. Due to the above described complexity, the LEWIS project involves several different research groups with different competences, and the experimental validation of the different parts of the system are carried out, by considering as monitoring scenarios three Italian highway sections recently involved in landslides phenomena. The L-band SDRadar module, fully realized into the Microwave Laboratory at University of Calabria, gives one of the most significant areal sensor of the system. Its schematic block diagram is shown in Fig. 2.
Fig. 2. Schematic configuration of L-band SDRadar system.
A Universal Software Radio Peripheral transceiver (NI USRP 2920) is adopted to replace most of the hardware operations through software implementation, thus significantly reducing the total cost of the areal sensor. In particular, the modulation and demodulation, mixing, signal generation and A/D and D/A conversions are performed without specific hardware devices. A Lab-View code, implemented on a compact PC (MXE 5302), controls the overall USRP operation. A horn antenna with a fixed position is adopted in the transmission path, while a patch array moved by a stepped motor, and having a configuration specifically designed for this application, is adopted in the receiving path. Two GSM modules are used for the communication between the device and the data collecting and control center, by adopting a protocol shared with the other devices of the LEWIS system. A photograph of the final configuration of the radar system is shown in Fig. 3, where a own designed compact receiving array antenna can be observed [6]-[7].
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Fig. 3. Photograph of the complete L-band SDRadar system.
Preliminary laboratory measurements carried out to validate the L-band SDRadar are described in [8]. In this work, the final experimental assessment on the operative scenario, including the radar installation and its complete integration with the LEWIS system, are fully described to prove the effective ability of monitoring landslide movements.
3 Experimental Results on A3 Highway in Calabria (Italy) In recent years, a specific hill side in proximity of the national A3 highway (Mancarelli, Calabria, Italy) is being frequently interested by landslides events with significant damages for road pavement and vehicles passing through. This particular area (39.2545°N, 16.2722°E) is chosen in the framework of LEWIS project to be monitored by the L-Band SDRadar. A photograph of the structure containing all the instrumentation of the radar system is shown in Fig. 4(a), while the position of the areal sensor with respect to the monitoring area (divided into 5 different sectors, each one corresponding to an azimuthal rotation of the receiving antenna, considering a 10° scan angle between two successive positions), is shown in Fig. 4(b).
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Fig. 4. (a) Shelter structure for radar installation and (b) position of the areal sensor with respect to the monitoring area.
For each sector, a High Range Resolution (HRR) profile, obtained by a Stretch Processing Technique [9], is elaborated, stored and transmitted to the control center for evaluating possible landslide events. In Fig. 5, the measured HRR profiles of the described monitored area on the five sectors, for different consecutive acquisitions at 5 min time steps, are reported.
Fig. 5. HRR profiles obtained through experimental test on the A3 highway scenario in Calabria, Italy.
The absolute variations in the HRR profile cannot be easily related to a critical movement of the monitored scenario. As a matter of fact, the backscattered power received from the scene depends on the radar cross section, the orientation and the reflectivity of the target. Furthermore, the absolute value of the received signal is also affected by the path loss, so this effect should be properly considered to effectively evaluate the target backscattering. In order to perform a useful quantitative estimation, an ad hoc estimator ξi(r), taking into account the relative variation of two successive profiles (i-1,i), and weighted with respect to the maximum value of the profile and the distance r, is introduced in this work. First of all, the relative power variation εi(r) between two range profiles, respectively equal to Si-1(r) and Si(r), is defined by the following expression: ߝ ሺݎሻ ൌ
ௌ ሺሻమ ିௌషభ ሺሻమ
(1)
ௌషభ ሺሻమ
In order to assign more relevance to the relative variation of higher values in the profile, another term is considered in this evaluation as providing the normalized power ܵመ ሺݎሻ:
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ܵመ ሺݎሻ ൌ
ௌ ሺሻమ ௫ሼௌ ሺሻమ ሽ
(2)
The last term considered in the analysis is the normalized distance ݀መ ሺݎሻ with respect to the total observation range, in order to compensate the effect of the path loss on the data observation, namely: ݎ (3) ݀መ ሺݎሻ ൌ ݉ܽݔሼݎሽ The value of the estimator ξi(r) is defined as the product of the above three terms, by considering a -2 exponent for the normalized distance, in order to contrast the quadratic decreasing of the power signal due to the path loss, namely: ߦ ሺݎሻ ൌ ߝ ሺݎሻݏƸ ሺݎሻ݀መ ሺݎሻିଶ
(4)
The estimator (4) is computed for each sector, considering the range profiles obtained in Fig. 5, and the results of this elaboration are reported in Fig. 6.
Fig. 6. Evolution of the estimator ξ between two successive time steps.
Some variations can be mainly observed in the range profiles elaborations of Fig. 6 for the Sectors 1-2, namely those directly facing the landslide scenario. They reveal some kind of dynamic changes in the observed scene, which however cannot be attributed to possible significant landslide movements, as all estimator values maintain below the prescribed limit of 50% variation. In order to advise a possible risk event, the above limit should be exceeded, with the risk level related to the range extension within which the limit overcome happens.
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4 Conclusions The experimental assessment of an SDRadar system for landslides monitoring has been described in this work. After the complete integration of the radar into the LEWIS system [5], a set of tests on a real Italy (Calabria) scenario involved few years ago in landslide events have been carried out, and a mathematical estimator useful for the proper detection of landslide movements is defined and applied to the measured range profile. The obtained preliminary results have revealed the usefulness of the proposed radar monitoring approach. A more extensive measurement campaign will be performed in future work, and a comparison with theoretical models for lansdlides prediction and analysis will be performed to further assess the proposed approach.
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