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Impact of Sensor Fusion on the Aerospace Sector


Impact of Sensor Fus

iCrowdNewswire   Sep 17, 2020  11:37 AM ET

Aircraft navigation is one of the most promising applications for sensor fusion. Most current navigation systems rely on a combination of GPS, inertial measurement units (IMUs), and sometimes other navigation sensors to provide accurate positioning and navigation information.

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Aerospace is a key market for sensor fusion including direct fusion, indirect fusion, and data fusion with multi-sensor, primarily for defense applications. Implementation for defense applications will also impact the commercial aircraft in the longer term. Enhanced vision systems such stereoscopic vision developed by fusing data from image sensors, multispectral imagers, and RADAR/LiDAR systems are expected to have the highest impact in the near-to-medium term. The development of platform technologies, which allows diverse sensors to be integrated in a plug-and-play manner for information fusion will boost the adoption of sensor fusion.

The U.S. is leading the development of Sensor Fusion for Aerospace applications with considerable push from the government to maintain leadership in aerospace and defense technologies.

Aircraft navigation is one of the most promising applications for sensor fusion. Most current navigation systems rely on a combination of GPS, inertial measurement units (IMUs), and sometimes other navigation sensors to provide accurate positioning and navigation information. It is imperative to develop systems that do not rely on GPS to prepare for situations where the sensor is not functional. Fusion of data or data fusion from GPS, IMUs, and data from outside entities are commercialized in the form of synthetic and enhanced vision systems.

Monitoring of various components using sensor fusion algorithms improves accuracy. These systems can enhance the detection of part failure and cracks as well as irregularities that can signify component failures at an early stage. With the proliferation of unmanned aerial vehicle (UAV) and the increase in terrorist activities, it is becoming increasingly vital to counter these airborne threats to commercial aircraft. Sensor suites that identify incoming projectiles are crucial for taking evasive action or undertaking countermeasures.

Sensor fusion allows better control of flights and provides automated capabilities. Platform technologies that are able to fuse a multitude of data from diverse sensors and information sources will be critical in providing advanced control options for the aircraft. Advanced vision systems are already being implemented in a host of aircraft. Integration of diverse sensors including terahertz (THz) sensors and multispectral imagers have a lower TRL.

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Amongst the various components being monitored, aircraft engines appear to be a top priority. The focus is on using wireless sensor networks that can transmit the data to a central hub for processing. Holistic monitoring of aircraft using sensor fusion is still in the research phase and is yet to experience technology demonstration.

The goal is to enable data from multiple aircraft and land/marine vessels to be fused to provide greater degree of accuracy in navigation and environment sensing. At least two data streams should be fused to provide greater accuracy such as hyper-spectral imaging + LIDAR, multispectral imaging + RADAR, and other combinations. The data is combined with navigational sensors and projected to enhance a pilot’s understanding of the environment. This becomes more desirable in challenging environmental conditions, including low visibility.

Using sensor fusion for enhanced navigation capabilities is a major focus area in the aerospace sector. Here, apart from data fusion, the use of packaged sensors consisting of multiple sensors, such as accelerometers and gyroscopes is also considered.

Sensor fusion helps in enhanced monitoring of various components or parameters – this includes monitoring of wear and tear, cargo, engines, and equipment. The probabilistic approach using filters, such as Bayesian and Kalman filters, is predominantly being used for the fusion of imperfect data.

Advanced vision systems based on sensor fusion have the highest probability of success. This technology is being already implemented in various degrees. However, more advancements are expected in the next 5 to 10 years, enabling enhanced visibility for pilots and facilitating assessment of runways and obstacles.

The number of patents filed for aerospace applications is considerably low compared to other applications of sensor fusion. This is primarily due to the higher potential in terms of volume that markets such as consumer electronics offer. The majority of the patents are targeted primarily at automotive applications with potential applicability in the aerospace sector. Maximum patents has been filed in the U.S.; this indicates the potential of the technology in this region. Minimal patent activity is witnessed in the APAC region due to the lack of global commercial aerospace technology developers.

Location tracking using sensor fusion as an alternative to GPS is likely to have a high impact in the long term. The technology will enable safer air transportation as well as track aircraft with greater precision.

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Email: sales@automo.ai
Website: https://automo.ai/
Phone: (+1) 113025664665






Keywords:    Sensor Fusion, Aerospace, Automotive, Unmanned Aircraft Systems, stereoscopic vision, direct fusion, indirect fusion, multi-sensor, data fusion, information fusion

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