Right, let me get back to you in a hour.
*For 'maturity' I am talking about IOC and FOC in the operational sense.
*Sensor fusion is not American sale tricks. In fact, it is F35's one of the most defining and defined aspect that has been shared in details.
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The next step in fusion technology was to combine the output of multiple sensor tracks into a blended system solution. By blending the tracks from two or more sensors, the resultant system track accuracy approached the accuracy of the best parameter of the contributing sensors. For example, blending tracks from a radar and an infrared search and track (IRST) sensor could have the range and range rate accuracy of the radar along with the angle and angle rate accuracy of the IRST. However, the accuracy of the resultant track remains limited by the track’s update rate. If the track’s update rate (fusion rate) is larger than the measurement’s rate, then there is a loss of accuracy, even with optimal algorithms [13].
US 5th Generation aircraft are designed to process the sensor measurements rather than the sensor tracks, resulting in an integrated system track containing the most precise track accuracy and enabling cooperative sensing across aircraft. Measurement-level processing can provide earlier discovery of objects in the environment that are hard to detect. By processing the measurement-level data, the system can use detections from any sensor (or aircraft) to confirm a track before any single sensor can make the declaration. The focus on the measurement data rather than track data also means that combat ID information from a sensor is retained by the system track, even when the track is no longer in the sensor’s field of view since the system track can be maintained by other sensors or aircraft.
In addition to improved accuracy and detection performance, the introduction of an Autonomous Sensor Management capability provided the ability to react and refine objects in the environment much faster than any human could respond [14]. The addition of the Autonomous Sensor Manager is referred to as Closed Loop Fusion. This capability provides the fusion process a feedback loop to coordinate the actions of the sensors in a complementary way to detect, refine, and maintain tracks based on system priorities [15]. The sensor management capability evaluates each system track, determines any kinematic or ID needs, assesses those needs according to system track prioritization, and cues the sensors to collect the required information. Analogous to John Boyd’s Observe, Orient, Decide, and Act (OODA) Loop [16], which expressed the engagement advantage related to the pilot’s ability to understand and react to an adversary, closed loop fusion accelerates the ability of the pilot to understand and respond to an object in space faster and often at a much greater range than legacy systems.
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The F-35 Information Fusion design isolates fusion algorithms from both the sensor and datalink inputs, as well as any consumers of fused data. Essentially, the fusion algorithms comprise a black box, known internally as the fusion engine, and sensor inputs and data consumers are encapsulated in external software objects known as virtual interface models (VIMs). For incoming data, the sensor-specific or datalink-specific VIMs fill in missing data (e.g., navigation state, sensor bias values), preprocess the information, and translate it into a standard form for the fusion process. For data leaving fusion, the outgoing VIM, known internally as the fusion server, provides data to the various consumers of fused information, both onboard and off-board. The fusion server isolates users of the fused information from both the fusion process and data sources. Legacy fusion implementations reported fusion tracks as a monolithic block (i.e., one size fits all) where all data consumers received the same message. Any propagation of the data or conversion was the responsibility of the recipient. This created a coupled interface between fusion and the data consumers. When a new data source was introduced to fusion, the interface changes to make this data available impacted all consumers of that message, whether the data was used or not, making changes to fusion very costly. The fusion server sends each information consumer a tailored message that contains only the information required to support that consumer. This isolates that consumer from changes to any data source or to the fusion algorithm. The use of VIMs enables the fusion architecture to be extensible to new sensors and data sources, as well as new data consumers, over its lifetime.
Information Tiers
“Sensor fusion can result in poor performance if incorrect information about sensor performance is used: A common failure in data fusion is to characterize the sensor performance in an ad hoc or convenient way. Failure to accurately model sensor performance will result in corruption of the fused results.” [17] One of the key architecture decisions for F-35 fusion is how to share information among aircraft. Independent data can be incorporated optimally into a filter for the highest accuracy. However, if dependent data is incorporated under the assumption of independence, the result will be track instability and, eventually, track loss [18]. Data consumers on the F-35, including the pilot, receive the kinematic and ID estimate of each track based on all available data sources, both onboard and off-board. This is referred to as the Tier 3 solution. However, when sharing information with other aircraft, each F-35 shares the information describing a track based solely on measurements from onboard sensors. This is referred to as the Tier 1 solution. By ensuring that the information received from MADL is independent, the track information can be converted into equivalent measurements [19] by the recipient supporting both track-to-track and
measurement-to-track of the information. The sharing of Tier 1 data ensures that the information is not coupled to any specific fusion algorithm and provides a method for dissimilar fusion platforms to share optimal fusion data in the future (Fig. 5). In late 2016, Lockheed Martin and the U.S. government used this technique to share an F-35 fused track of a target drone across MADL to a surface-based weapons system that had no line of sight to the drone. The surface-based weapons system converted the F-35 MADL Tier 1 information into equivalent measurements that were consumed by the native engagement tracker. Together, the networked systems achieved a successful acquisition, guidance, and kinematic intercept of the track using a surface-to-air missile.
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There are more details on
Evidence-Based Combat Identification, autonomous sensor management and
cooperative sensing, including the operative equations in the article below.
They have provided as much details possible on the system architecture, and functionalities without getting into classified stuff.
On the other hand, with KAAN or Chinese 5th gen platform none of its clear for now. They just say the words like sensor fusion, AI, etc. However without providing any basic information on the system's architecture and functionalities.
The reason people doubt the degree of J20 or KAAN's sensor fusion (at this point) and whether it is comparable to latest F35, is because it took decades even for US to develop a sensor fusion engine like that in the JSF. Despite having the most expertise and spending the most resources. Now others coming along the line and just claiming, oh we have the best sensor fusion too, without providing any comparable infos and details is not convincing enough.
Both in case of KAAN and J20, until there more details available on the architecture type and the functionalities of fusion engine of each platform, their comparability with F35 will be justifiably doubted. Mere broad claims are not good enough here.
That's why I am suggesting to wait until the later blocks of KAAN are operational before directly comparing it to the latest F35 block 4.
www.defenseone.com
www.airandspaceforces.com
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