<p> This thesis investigates the processing of emergency locator transmitter (ELT) signals which are used in search and rescue satellite-aided tracking (SARSAT) systems. Essentially, the system relies on the transmission of ELT signals from a distressed platform being relayed through an orbiting satellite to an earth station where signal processing can be performed. </p> <p> The methods of signal processing investigated here include both linear and nonlinear. The linear methods include the window function, the autocorrelation function, the digital filtering and the Fast Fourier Transform (FFT). The nonlinear processing is based on the Maximum Entropy Method (MEM) . In addition, additive white Gaussian noise has been added to simulate the performance under different carrier-to-noise density ratio conditions. </p> <p> For a single ELT signal, it is shown in the thesis that the MEM processor gives good spectral performance as compared to the FFT when applied to all types of modulation. When multiple ELT signals are present, the MEM also provides certain benefits in improving the spectral performance as compared to the FFT. </p> / Thesis / Master of Engineering (ME)

The work summarized in this report aims to investigate how a drone airplane design can be optimized to create a safer and more efficient sea rescue by providing staff with an early picture, performing search missions and aiding communication through visual contact. A flying wing is in theory one of the most efficient designs for a fixed wing aircraft, at the same time as it also offers high structural efficiency for its given size. In this report, an overview of aerodynamics, stability and flying quality for a flying wing is discussed and analysed. XFLR5 was used for this project, and a comparison between the analytical results and wind tunnel test data for a prototype was conducted. A strong correlation was found between the theoretical analyses and the wind tunnel data. A simple control solution using only one set of elevons has been proposed and simulated, resulting in Level 1 dynamic stability for all modes except Dutch-roll (where the drone’s damping is 𝜁𝑑𝑟=0.07 and the requirement for Level 1 is 𝜁𝑑𝑟=0.08). For the range of angle of attack used, the autopilot system will have to trim the drone in flight to achieve stability. As the drone only has one set of control surfaces there will be a loss of efficiency in this scenario, meaning that 𝐶𝐿/𝐶𝐷 = 15.7 for loiter speed of 15 𝑚/𝑠 and 7.9 for full speed at 35 𝑚/𝑠. In regular flight, with a total mass &lt;1 𝑘𝑔, the drone is able to fly at full speed for 214 𝑘𝑚 or loiter for 6.3 ℎ with a battery package of 130 𝑊ℎ. As such, the objective of this project was achieved, and the proposed design met the given requirements. / betet som sammanfattas i denna rapport syftar till att undersöka huruvida ett drönar-flygplan bäst kan utformas för att skapa en säkrare och effektivare sjöräddning genom att ge räddningspersonalen en tidig överblick, utföra sökuppdrag och bistå till kommunikation genom visuell kontakt. En flygande vinge är i teorin en av de mest effektiva konstruktionerna för ett flygplan, likaså erbjuder den en hög strukturell effektivitet för en given storlek. I denna rapport diskuteras och genomförs en översikt över aerodynamik, stabilitet och flygkvalitet hos en flygande vinge. XFLR5 användes för detta projekt, och en jämförelse mellan analysresultaten och ett vindtunneltest med en prototyp genomfördes. I allmänhet är överenskommelsen mellan de teoretiska analyserna och vindtunneldatan god. En enkel lösning som enbart består av en uppsättning kontrollytor har föreslagits och simulerats, vilket resulterar i en Nivå 1 dynamisk stabilitet för alla lägen utom Dutch-roll, där drönarens dämpning är 𝜁𝑑𝑟 = 0.07 och kravet för Nivå 1 är 𝜁𝑑𝑟 = 0.08. Autopilotsystemet behöver trimma drönaren under flygning för att uppnå nödvändig stabilitet för det spann av attackvinklar som används, med endast en uppsättning kontrollytor, vilket minskar effektiviteten för BWB-drönaren till 𝐶𝐿/𝐶𝐷=15.7 för cirkuleringshastigheten på 15 𝑚/𝑠 och 7.9 för full hastighet vid 35 𝑚/𝑠. Drönaren kan flyga i full hastighet i 214 𝑘𝑚 eller cirkulera runt olycksplatsen under 6.3 timmar med ett batteripaket på 130 𝑊ℎ, med en vikt som är lägre än 1 𝑘𝑔. Målen med detta projekt uppnåddes och drönaren utformades enligt kraven.

With unmanned aerial vehicle(s) (UAV), swift responses to urgent needs (such as search and rescue missions or medical deliveries) can be realized. Simultaneously, legislators are establishing so-called geographical zones, which restrict UAV operations to mitigate air and ground risks to third parties. These geographical zones serve particular safety interests but they may also hinder the efficient usage of UAVs in time-critical missions with range-limiting battery capacities. In this study, we address a facility location problem for up to two UAV hangars and combine it with a routing problem of a standard UAV mission to consider geographical zones as restricted areas, battery constraints, and the impact of wind to increase the robustness of the solution. To this end, water rescue missions are used exemplary, for which positive and negative location factors for UAV hangars and areas of increased drowning risk as demand points are derived from open-source georeferenced data. Optimum UAV mission trajectories are computed with an A* algorithm, considering five different restriction scenarios. As this pathfinding is very time-consuming, binary occupancy grids and image-processing algorithms accelerate the computation by identifying either entirely inaccessible or restriction-free connections beforehand. For the optimum UAV hangar locations, we maximize accessibility while minimizing the service times to the hotspots, resulting in a decrease from the average service time of 570.4 s for all facility candidates to 351.1 s for one and 287.2 s for two optimum UAV hangar locations.

Search and rescue operations conducted in wilderness environments can be greatly aided by the use of video filmed from mini-UAVs. While lightweight, inexpensive and easily transportable, these small aircraft suffer from wind buffeting and may produce video that is difficult to search. To aid in the video search process, we have created a system to project video frames into a 3D representation of the search region. This projection allows us to tie each frame of video to a real-world location, enabling a myriad of novel views, mosaics and metrics that can be used to guide the search including a new metric dubbed “see-ability.” The “see-ability” metric is the primary contribution of this research as it indicates what portion of the search area has been viewed and provides an estimate of the quality of that viewing. The research includes a validation of the “see-ability” metric as it correlates to objective performance in the search task by real people.

This thesis aims to contribute to ethical discussions on the production of photography in different humanitarian contexts, and in circumstances where it is facilitated by non-governmental and international non-governmental organisations (I/NGOs). Humanitarian photography is often reproduced and circulated in various forms by different actors, highlighting the need for research on the actions, decisions, and interactions that influence how these images are produced. An extensive literature review captures the many ethical challenges surrounding humanitarian photography and provides an overview of related standards. A conceptual framework is then built around informed consent as an accountability mechanism, with consideration for certain relational and situational factors that influence the quality and effectiveness of the process of obtaining consent. Emphasising photographer and organisational accountability, an analysis of how photographers apply the concept of informed consent and its potential as an accountability mechanism is explored through the case study of embedded photographers in search and rescue (SAR) I/NGO operations in the Mediterranean Sea.     Four semi-structured in-depth interviews were completed with photographers involved in SAR I/NGO missions in the Mediterranean from 2015 to 2021. The interviews suggest that a continuous and deliberate process of individual, organisational, and collaborative self-regulation unfolds throughout a mission, largely through verbal communication and body language, in an effort to obtain consent to take or use images of people who have been rescued. Use of formal means such as written consent forms are only rarely used. Photographs during the rescues were generally taken without prior consent, and photographers’ ability to obtain meaningful subsequent informed consent was easily compromised due to the unpredictable conditions during SAR operations and the variation across I/NGO-photographer partnerships. These findings support the need for further dialogue in this context to ensure that practices and processes related to the production of humanitarian photography, such as obtaining informed consent, are compatible with humanitarian principles, respect the rights and dignity of people affected by crisis, and foster greater accountability.

Sjöräddning i Sverige sker genom samverkan mellan statliga verksamheter, kommuner och frivilligorganisationer för ett gemensamt mål att rädda personer som råkat i sjönöd. Tid är ofta en kritisk faktor i räddningsuppdragen men ett snabbt och oplanerat utryck riskerar samtidigt att sätta räddningsaktörerna själva i farozonen. Utvecklingen av obemannade autonoma farkoster för SAR (eng. Search And Rescue) ses som en lösning på behovet att kunna snabbt skicka hjälp till samt få ögon på incidentplatsen utan att försätta räddningsaktörerna för onödig risk. Nuvarande kommunikationssystem inom svensk sjöräddning kan dock inte hantera annan typ av information än muntlig varav räddningsaktörer endast känner till riktlinjer för hantering av muntlig information. Med ett framtida införande av autonoma farkoster kommer dock fler informationstyper att behöva hanteras i sjöräddningar varav oklarheten om vilka informationstyper autonoma farkoster samlar in och vilka datahanteringskrav som finns är problematiskt. Oklarhet om informationstyperna och deras datahanteringskrav är vidare problematiskt för utvecklingen och implementeringen av autonoma farkoster då risken finns att farkoster och tekniker utvecklas men inte får användas för att de inte är anpassade efter lagkraven på hantering av olika datatyper. I denna studie undersöks därför vilka informationstyper som autonoma farkoster kan samla in vid sjöräddning. Detta för att komma fram till vilka riktlinjer för datahantering som gäller vid sjöräddning med autonoma farkoster. Studien undersöker också vilka informationstyper som är kritiska för en SAR-sjöräddningssamverkan samt vilka informationsdelningsutmaningar som finns i dagens sjöräddning. Studien genomfördes i form av en kvalitativ fallstudie och har tillämpat ett socio-tekniskt systemperspektiv för att bättre se till helheten och besvara frågeställningarna. Resultatet av denna studie visar att autonoma farkoster kan samla in information om sin omgivning, vilket utgör grunden för att skapa en medvetenhet om situationen som är kritiskt för SAR-operationer, och kan även samla in information om sitt eget tillstånd. De lagverk som identifierats utgöra de huvudsakliga restriktionerna är kamerabevakningslagen, lagen för skydd av geografisk information, offentlighets- och sekretesslagen, GDPR och dataskyddslagen. Dessa lagverk innehåller riktlinjer för delning av information och personuppgiftsbehandling i SAR-sjöräddning. Kunskapsbidrag studien har genererat inkluderar bland annat identifiering av datatyper som kan samlas in av autonoma farkoster i en SAR-sjöräddning, och sannolikt andra typer av räddningsinsatser, och delning och hanteringskraven på de datatyperna i räddningsinsatser och därmed kunskap om vilka datatyper som är mest reglerade. Vidare kunskapsbidrag är kunskap om vilka informationstyper som är mest kritiska för SAR-sjöräddningar, och därför bör prioriteras att samlas in och delas, och identifieringen av utmaningar för informationsdelning mellan statliga verksamheter och frivilligorganisationer. / Maritime rescue in Sweden is performed through a cooperation between government agencies, municipalities and non-governmental organisations (NGOs) with the common goal of saving people in distress. Time is often a critical factor in the rescue missions but a fast and unplanned response may at the same time put the rescue workers in danger. The development of unmanned autonomous vehicles for SAR is seen as a solution to the need of being able to quickly sendhelp as well as get eyes on the scene of the incident without exposing the rescue workers for unnecessary risks. However, the current communications systems in Swedish maritime rescue are unable to handle any other type of information except verbal, meaning that rescue workers only know guidelines for handling verbal information. However, with a future implementation of autonomous vehicles, there will be a need to handle more information types in maritime rescue whereas the uncertainty regarding what kind of information autonomous vehicles collect and which data management requirements exist is problematic. The uncertainty about the information types and their data management requirements is also problematic for the development and implementation of autonomous vehicles as there is a risk that vehicles and technologies are developed but not allowed to be used because they are not adapted to the legal requirements on management of the different types of data. Therefore, in this study I examine what information types that autonomous vehicles can collect in a maritime rescue to find out what guidelines for data management that applies during a maritime rescue with autonomous vehicles. The study also examines what kind of information’s are critical for a SAR maritime rescue cooperation as well as what information sharing challenges exist in current maritime rescue. The study was performed as a qualitative case study and has used a socio-technical systems perspective so as to better see the overall picture and answer the research questions. The result shows that autonomous vehicles can collect information about their surroundings, which is the foundation for establishing situation awareness that is critical for SAR-operations, and that they can collect information about their own status. The main laws and regulations that have been identified as constituting the main restrictions are (translated from Swedish) the law of camera surveillance, the law for protection of geographical information, the public access to information and secrecy act, the GDPR and the data protection act. These contains guidelines for sharing information and the processing of personal data in SAR maritime rescue. The knowledge contributions of this study includes among others the identification of datatypes that can be collected by autonomous vehicles in SAR maritime rescue, and probably other types of rescue operations, and the sharing and management requirements on those datatypes in rescue operations and thus knowledge of what datatypes that are the most restricted. Further knowledge contributions is knowledge about which information types that are the most critical for SAR maritime rescue and thus should be prioritised for collection and sharing as well as the identification of challenges for information sharing between government agencies and NGOs.

Following unprecedented earthquakes in 1999, highly centralized Turkey initiated reforms that aimed to improve disaster management collaboration and to empower local authorities. In 2011, two earthquakes hit the country anew affecting the city of Van and town of Erciş in Turkey’s southeast. In attempts to reduce disaster risk, global disaster risk reduction frameworks and disaster scholars and practitioners advocate collaborative and decentralized disaster management strategies. This thesis investigates how such strategies are received in a centralized and hierarchical national political-administrative system that largely is the anti-thesis of the prescribed solutions. More specifically, this research investigates the barriers and prerequisites for disaster management collaboration between both public and civil society actors in Turkey (during preparedness, response, and recovery) as well as how Turkey’s political-administrative system affects disaster management collaboration and its outcomes. The challenges to decentralization of disaster management are also investigated. Based on forty-four interviews with actors ranging from national to village level and NGOs, the findings suggest that the political-administrative system can alter the relative importance, validity, and applicability of previously established enabling or constraining conditions for collaboration. This may in turn challenge previous theoretical assumptions regarding collaboration. By adopting a mode of collaboration that fit the wider political-administrative system, collaborative disaster management progress was achieved in Turkey’s national level activities. Although there were exceptions, collaboration spanning sectors and/or administrative levels were generally less forthcoming, partly due to the disjoint character of the political-administrative system. Political divergence between local and central actors made central-local collaboration difficult but these barriers were partly trumped by other prerequisites enabling collaboration like interdependence and pre-existing relations. The findings suggest that the specific attributes of disasters may both help and hinder disaster management collaboration. Such collaboration generally improved disaster response. The findings also indicate that the decentralization attempts may have been premature as the conditions for ensuring a functional decentralization of disaster management are presently lacking. Decentralization attempts are commonly suggested to increase local capacity and local participation but the findings of this dissertation suggest that in Turkey, these commodities may currently have better chances of being increased by refraining from decentralization.

CAPES / Este trabalho tem como objetivo propor um método reconhecimento de pessoas em imagens aéreas obtidas a partir de Veículos Aéreos Não Tripulados de pequeno porte. Esta é uma aplicação de grande interesse, pois pode ser inserida em diversas situações tanto civis quanto militares como, por exemplo, missões de busca e salvamento. O uso de Veículos Aéreos Não Tripulados autônomos tende a aumentar com o barateamento desta tecnologia. Assim, esta tecnologia pode sobressair sobre outras utilizadas atualmente, como satélites e voos com grandes aeronaves. Para o reconhecimento de pessoas em imagens aéreas de forma autônoma, este trabalho propõe métodos na forma de Sistemas de Reconhecimento de Padrões (SRP) aplicados ao reconhecimento de imagens. Para este métodos, foram testadas quatro técnicas de aprendizado de máquina: Redes Neurais Convolucionais, HOG+SVM, Cascata Haar e Cascata LBP. Além disso, a fim de possibilitar o reconhecimento de pessoas em imagens aéreas em tempo real, foram testadas e avaliadas técnicas de detecção e segmentação de objetos: Mapa de Saliências e o Processamento de Imagens Térmicas de baixa resolução (PIT). Neste trabalho foram avaliadas as taxas de reconhecimento dos SRPs, além do seu tempo de processamento em um sistema embarcado de baixo custo e em uma Base de Controle Móvel (BCM). Os resultados de reconhecimento mostraram a efetividade das Redes Neurais Convolucionais, com uma acurácia de 0,9971, seguido do HOG+SVM com 0,9236, Cascata Haar com 0,7348 e por fim, Cascata LBP com 0,6615. Em situações onde foi simulado a oclusão parcial, as Redes Neurais Convolucionais atingiram Sensibilidade média 0,72, HOG+SVM de 0,50 e as Cascatas 0,20. Nos experimentos com os SRPs (algoritmos de segmentação e detecção juntamente com as técnicas de reconhecimento), o Mapa de Saliências pouco afetou as taxas de reconhecimento, quais ficaram muito próximas das obtidas no experimentos de reconhecimento. Já o Processamento de Imagens Térmicas de baixa resolução apresentou dificuldades em executar uma segmentação precisa, obtendo imagens com variação na translação, prejudicando a precisão do sistema. Por fim, este trabalho propõe uma nova abordagem para implementação de um SRP para o reconhecimento de pessoas em imagens áreas, utilizando Processamento de Imagens Térmicas juntamente com as Redes Neurais Convolucionais. Este SRP une altas taxas de reconhecimento com desempenho computacional de ao menos 1 fps na plataforma BCM. / This work aims to propose a method for people recognition in Small Unmanned Aerial Vehicles aerial imagery. This is an application of high interest, it can be used in several situations, both civilian and military, as search and rescue missions. The use of Unmanned Aerial Vehicles autonomously tends to increase with the cheapening of this technology, supporting search and rescue missions. Thus, this technology can excel over others currently used, as satellites and flights with large aircraft. For autonomous people recognition, this work proposes new methods as Pattern Reconigition System (PRS) applied to image recognition, applying it in aerial images. Four Pattern Reconigition techniques were tested: Convolutional Neural Networks, HOG+SVM, Haar Cascade and LBP Cascade. Furthermore, in order to achieve recognition of people in aerial images in Real-Time target and detection techniques were tested and evaluated: Saliency Maps and Low-resolution Thermal Image Processing (TIP). In this work were considered recognition rates of the methods and their computational time in a low-cost embedded system and a Mobile Ground Control Station (MGCS). The recognition results shown the Convolutional Neural Network potential, where an accuracy of 0.9971 was achieved, followed by HOG + SVM with 0.9236, Haar Cascade with 0.7348 and LBP Cascade with 0.6615. In situations simulated partial occlusion, where was the CNNs achieved average Sensitivity of 0.72, HOG+SVM with 0.50 and both Cascades 0.20. In experiments with PRS (targeting and detection algorithms with the recognition techniques), the Saliency Map had little influence in recongition rates, it was close to the rates achieved in recognition experiments. While the Low-resolution Thermal Image Processing had difficulties in segmentation process, where translation variantions occured, it harmed the system precision. Lastly, this work proposes a new approach for PRS implementation for people recognition in aerial imagery, using TIP with CNN. This PRS combines high rates of recognition with an computational performace of, at least, 1 fps in MGCS plataform.

CAPES / Este trabalho tem como objetivo propor um método reconhecimento de pessoas em imagens aéreas obtidas a partir de Veículos Aéreos Não Tripulados de pequeno porte. Esta é uma aplicação de grande interesse, pois pode ser inserida em diversas situações tanto civis quanto militares como, por exemplo, missões de busca e salvamento. O uso de Veículos Aéreos Não Tripulados autônomos tende a aumentar com o barateamento desta tecnologia. Assim, esta tecnologia pode sobressair sobre outras utilizadas atualmente, como satélites e voos com grandes aeronaves. Para o reconhecimento de pessoas em imagens aéreas de forma autônoma, este trabalho propõe métodos na forma de Sistemas de Reconhecimento de Padrões (SRP) aplicados ao reconhecimento de imagens. Para este métodos, foram testadas quatro técnicas de aprendizado de máquina: Redes Neurais Convolucionais, HOG+SVM, Cascata Haar e Cascata LBP. Além disso, a fim de possibilitar o reconhecimento de pessoas em imagens aéreas em tempo real, foram testadas e avaliadas técnicas de detecção e segmentação de objetos: Mapa de Saliências e o Processamento de Imagens Térmicas de baixa resolução (PIT). Neste trabalho foram avaliadas as taxas de reconhecimento dos SRPs, além do seu tempo de processamento em um sistema embarcado de baixo custo e em uma Base de Controle Móvel (BCM). Os resultados de reconhecimento mostraram a efetividade das Redes Neurais Convolucionais, com uma acurácia de 0,9971, seguido do HOG+SVM com 0,9236, Cascata Haar com 0,7348 e por fim, Cascata LBP com 0,6615. Em situações onde foi simulado a oclusão parcial, as Redes Neurais Convolucionais atingiram Sensibilidade média 0,72, HOG+SVM de 0,50 e as Cascatas 0,20. Nos experimentos com os SRPs (algoritmos de segmentação e detecção juntamente com as técnicas de reconhecimento), o Mapa de Saliências pouco afetou as taxas de reconhecimento, quais ficaram muito próximas das obtidas no experimentos de reconhecimento. Já o Processamento de Imagens Térmicas de baixa resolução apresentou dificuldades em executar uma segmentação precisa, obtendo imagens com variação na translação, prejudicando a precisão do sistema. Por fim, este trabalho propõe uma nova abordagem para implementação de um SRP para o reconhecimento de pessoas em imagens áreas, utilizando Processamento de Imagens Térmicas juntamente com as Redes Neurais Convolucionais. Este SRP une altas taxas de reconhecimento com desempenho computacional de ao menos 1 fps na plataforma BCM. / This work aims to propose a method for people recognition in Small Unmanned Aerial Vehicles aerial imagery. This is an application of high interest, it can be used in several situations, both civilian and military, as search and rescue missions. The use of Unmanned Aerial Vehicles autonomously tends to increase with the cheapening of this technology, supporting search and rescue missions. Thus, this technology can excel over others currently used, as satellites and flights with large aircraft. For autonomous people recognition, this work proposes new methods as Pattern Reconigition System (PRS) applied to image recognition, applying it in aerial images. Four Pattern Reconigition techniques were tested: Convolutional Neural Networks, HOG+SVM, Haar Cascade and LBP Cascade. Furthermore, in order to achieve recognition of people in aerial images in Real-Time target and detection techniques were tested and evaluated: Saliency Maps and Low-resolution Thermal Image Processing (TIP). In this work were considered recognition rates of the methods and their computational time in a low-cost embedded system and a Mobile Ground Control Station (MGCS). The recognition results shown the Convolutional Neural Network potential, where an accuracy of 0.9971 was achieved, followed by HOG + SVM with 0.9236, Haar Cascade with 0.7348 and LBP Cascade with 0.6615. In situations simulated partial occlusion, where was the CNNs achieved average Sensitivity of 0.72, HOG+SVM with 0.50 and both Cascades 0.20. In experiments with PRS (targeting and detection algorithms with the recognition techniques), the Saliency Map had little influence in recongition rates, it was close to the rates achieved in recognition experiments. While the Low-resolution Thermal Image Processing had difficulties in segmentation process, where translation variantions occured, it harmed the system precision. Lastly, this work proposes a new approach for PRS implementation for people recognition in aerial imagery, using TIP with CNN. This PRS combines high rates of recognition with an computational performace of, at least, 1 fps in MGCS plataform.

為維護海上人命、船舶及財產安全，各國均依「1982年聯合國海洋法公約」規定，建立區域搜救合作機制，並參考相關國際公約及搜救作業手冊，規範海上航行安全及緊急事故處理程序，惟因各國地理、水文及氣候不同，執行航行安全維護能力有限，皆必須透過多邊或雙邊搜救合作，強化區域航行安全，藉由搜救交流、兵棋推演或聯合演習等方式，提升彼此搜救合作默契及技能，以保障海上航行安全。 臺灣海峽自古以來即為東亞重要航道，兩岸航運亦自1987年開放兩岸探親，2001年金馬小三通，直至2008年正式海、空運直航以來，臺灣與大陸人民往來逐漸到達頂峰，而海難事故發生頻率亦不斷提高，藉此搜救合作契機在此為氛圍下形成，並在簽署「海峽兩岸海運協議」基礎上，透過輪流舉辦演練、搜救交流互訪及建立緊急聯繫管道等工作，逐步建立兩岸海上搜救合作機制，以「就近就便、及時救援」之原則，共同合作展現兩岸「人道救援」之普世價值。 在兩岸海上搜救合作機制下，兩岸搜救機關不斷共同執行海上搜救合作，增進彼此合作默契與搜救技能，但在兩岸分治的政治現實下，合作機制僅能透過民間團體的協助逐漸常態化，卻未能明文制度化，且隨著政治環境的轉變，搜救合作機制似有停頓，但海峽海域環境依然惡劣，往來人民持續熱絡，因此，為維護海峽航行安全，兩岸搜救機關仍應持續努力，共同完善合作機制，以確保兩岸人民生命財產安全。 / For the sake of maintaining people’s safety and property at sea, every coastal State establish the regional search and rescue (hereinafter SAR) cooperation mechanism in accordance with the United Nations Convention on the Law of the Sea, 1982, and formulate the navigation safety rules and standard operation procedure of responding to the emergency cases at sea. Due to the discrepancy of geography, hydrology and climate as well as limited ability for maintaining the navigation safety among counties, every state shall enhance the regional navigational safety by lateral or multilateral cooperation in SAR exchange, table-top exercise and joint SAR drill to strengthen the SAR cooperation mechanism and technique in order to provide the safe environment for navigation. Taiwan Strait is the pivotal shipping route of Eastern Asia through the ages. The shipping of the cross-strait starts from visit relatives between both sides in 1987, and gradually increases after the transport links between the Kinmen, Matsu areas and the Mainland area in 2001. The air and sea transport between Taiwan and Mainland area begin in 2008, and the number of Taiwanese and Chinese travel between Taiwan and Mainland reaches the highest record which leads to the increasing disasters at sea. In order to respond to this situation, the cooperation between the cross-strait are needed and the SAR drills are held in turns and officials’ visiting as well as emergency communication channel in accordance with the Cross-Strait shipment agreement which came into effect in 2008. Those measures concrete the SAR cooperation mechanism of the cross-strait on the basis of saving life and property at sea promptly when one side is close or ready for it and demonstrate the common vision of humanitarian rescue. According to the cross-strait’s SAR cooperation mechanism, the rescue authorities of both sides conduct the SAR mutually to enhance the coordination and SAR skills for their work. However, due to the politic relationship of the cross strait, the cooperation is under the non-official channel. Since the political change with the new government in Taiwan, the cooperation between Taiwan and Mainland China is suspended. The Taiwan Strait is a high risk area for people of both sides. Furthermore, in order to provide the safe navigational area, the cross-strait SAR authorities shall continuously establish the cooperative mechanism to maintain the people’s safety and their property.