Hyperwarp
Captain
Yup! Looks like we are back to square-one.
Edit: But I think the DF-41 values might reflect reality.
China Ballistic Missiles and Nuclear Arms Thread
- Thread starter peace_lover
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Yup! Looks like we are back to square-one.
Edit: But I think the DF-41 values might reflect reality.
Yup! Looks like we are back to square-one.
Edit: But I think the DF-41 values might reflect reality.
To be honest I think all of the numbers sound pretty sensible.
Sachant que même Mianyang démarre à peine les essais en soufflerie d'un glider HTV-2-like, on est pratiquement sûr que DF-ZF est de forme ≠.
Translated from French by
Knowing that same Mianyang starts barely a glider HTV-2-like wind-tunnel testing, we're pretty sure that DF-ZF is of the form ≠.
schlieffen
New Member
Fission devices are still widely used as low-yield tactical nuclear weapon. Most are of the boosted type which makes the yield adjustable. If we’re to believe information available on the public domain, modern miniature thermalnuclear weapons are also closer to super-boosted fission bomb as oppose to classical two-stage design.
Hendrik_2000
Lieutenant General
Here Henri take on the same subject. Henri guess it Shandong
According to a statement by the CETC group, a new radar, "important and the first of its kind in China," was admitted to active duty on September 27, 2016.
The exact type of radar was not disclosed by the text, but it specifies that it is a "historical" moment and an "important step in the construction of the overall system of the field". The text adds that several years were necessary between the design, construction, testing, calibration and the first experimental exploitation of the site.
The importance of this inauguration can also be illustrated by the fact that the Director of the ECCC Institute No. 14 - one of the two most important radar research offices in the country - attended the ceremony with all development team. According to some sources familiar with the case, several top Chinese Air Force (PLAAF) officials and an early warning missile unit were also involved.
In front of the radar in question (Source: ECCC)
In the only photo in the official statement, there are actually two people in uniform of the PLAA but it is difficult to identify them. However, given their relative young ages, they should be the radar operating personnel and not the senior officials in question.
Another photo of the ceremony (Source: ECCC)
It will also be noted in the photo that there are 19 men and women before it appears to be the base of a metal installation. If we count that the width of each person is 50cm, we are therefore in front of a structure that is at least 10 meters wide.
So what is this radar of such "capital importance"?
China's first anti-missile defense radar
By pooling several sources of information, the facility would actually be the first Chinese P-band early warning radar.
According to one of the academic papers written by researchers at ECET Institute No. 14, this radar is 30 meters in diameter and its operation requires that the flatness of the face of the radar be less than 3.8mm. As a result, the radar is cut into 60 rectangular dies of a dimension of 2 meters x 7.5 meters, ie a total area of 900m².
The summary image of the P-band early warning radar, extracted from a document of the ECCC Institute No. 14
The document also mentions a building where the radar is located, where each matrix is installed on a metallic steel box, with more than 2.5 tonnes of cables and equipment.
Although the exact location of this radar is not known, it is believed to be located on the Shandong Peninsula to monitor any ballistic launch from the east / south-east direction. vast area between the Korean Peninsula and Guam.
Its operation should be close to that of PAVE PAWS American, which allows the detection and characterization of ballistic missiles from the propelled phase to mid-race. The frequency used, between 225 and 390 MHz, means that the resolution of the radar does not make it possible to provide a firing solution, but the range is, on the other hand, very large, of the order of several thousand kilometers depending on the power provided.
BMEWS radars in Fylingdales, England (Source: Cherubino)
In order for the "global system" of missile defense to be complete, not only sufficient surveillance radars as we speak here are required, but also X-ray firing range radars as well as ABM missiles.
The inauguration of this first Early Warning Radar is therefore, as mentioned in the ECCC communiqué, a first step but far from being the last one. But the Chinese seem to be advancing step by step with , and .
Diagram taken from another university document showing the operation of ABM radars
If this first Chinese early warning radar is actually in Shandong, it will also mean that China believes that the threat is greater and more imminent from that part of the region, at least much more threatening than the leadership India and Russia.
30 years after - Project 640 - is the country prepared to carry out this year's ABM efforts that are very resource intensive but without any definite results?
The suite of constructions will certainly tell us more.
Henri K.
According to a statement by the CETC group, a new radar, "important and the first of its kind in China," was admitted to active duty on September 27, 2016.
The exact type of radar was not disclosed by the text, but it specifies that it is a "historical" moment and an "important step in the construction of the overall system of the field". The text adds that several years were necessary between the design, construction, testing, calibration and the first experimental exploitation of the site.
The importance of this inauguration can also be illustrated by the fact that the Director of the ECCC Institute No. 14 - one of the two most important radar research offices in the country - attended the ceremony with all development team. According to some sources familiar with the case, several top Chinese Air Force (PLAAF) officials and an early warning missile unit were also involved.
In front of the radar in question (Source: ECCC)
In the only photo in the official statement, there are actually two people in uniform of the PLAA but it is difficult to identify them. However, given their relative young ages, they should be the radar operating personnel and not the senior officials in question.
Another photo of the ceremony (Source: ECCC)
It will also be noted in the photo that there are 19 men and women before it appears to be the base of a metal installation. If we count that the width of each person is 50cm, we are therefore in front of a structure that is at least 10 meters wide.
So what is this radar of such "capital importance"?
China's first anti-missile defense radar
By pooling several sources of information, the facility would actually be the first Chinese P-band early warning radar.
According to one of the academic papers written by researchers at ECET Institute No. 14, this radar is 30 meters in diameter and its operation requires that the flatness of the face of the radar be less than 3.8mm. As a result, the radar is cut into 60 rectangular dies of a dimension of 2 meters x 7.5 meters, ie a total area of 900m².
The summary image of the P-band early warning radar, extracted from a document of the ECCC Institute No. 14
The document also mentions a building where the radar is located, where each matrix is installed on a metallic steel box, with more than 2.5 tonnes of cables and equipment.
Although the exact location of this radar is not known, it is believed to be located on the Shandong Peninsula to monitor any ballistic launch from the east / south-east direction. vast area between the Korean Peninsula and Guam.
Its operation should be close to that of PAVE PAWS American, which allows the detection and characterization of ballistic missiles from the propelled phase to mid-race. The frequency used, between 225 and 390 MHz, means that the resolution of the radar does not make it possible to provide a firing solution, but the range is, on the other hand, very large, of the order of several thousand kilometers depending on the power provided.
BMEWS radars in Fylingdales, England (Source: Cherubino)
In order for the "global system" of missile defense to be complete, not only sufficient surveillance radars as we speak here are required, but also X-ray firing range radars as well as ABM missiles.
The inauguration of this first Early Warning Radar is therefore, as mentioned in the ECCC communiqué, a first step but far from being the last one. But the Chinese seem to be advancing step by step with , and .
Diagram taken from another university document showing the operation of ABM radars
If this first Chinese early warning radar is actually in Shandong, it will also mean that China believes that the threat is greater and more imminent from that part of the region, at least much more threatening than the leadership India and Russia.
30 years after - Project 640 - is the country prepared to carry out this year's ABM efforts that are very resource intensive but without any definite results?
The suite of constructions will certainly tell us more.
Henri K.
Hendrik_2000
Lieutenant General
They send couple of mysterious satellite for "crop and scientific surveillance". Generally nobody know because they are very secretive.But this new P band radar has Anti missile function This morning Henri K blog. China is in process of developing 3 layer of radar coverage P. X,OTH band
China has just revealed what its new radar early warning missile defense, installed at the top of the mounts in Shandong province, looks like in a public exhibition in Beijing.
This huge electronic scanning radar measuring 30 meters in diameter was inaugurated on September 27, 2016, without a drum or trumpet, but in the presence of several senior officials of the Chinese Air Force (PLAAF) as well as representatives of the constructor NRIET and an anti-missile early warning unit.
We spoke about this inauguration in the case of " " last year and gave some technical details of this early warning radar in " ".
China's anti-missile warning radar is displayed in an exhibition in Beijing
The inscription of the image indicates that this radar administered by the PLAAF is in fact operating in the P band, a frequency range (from 225 to 390 MHz) also used by the PAVE PAWS radar of the American Army.
The image also confirms that the surface of the radar is cut into numerous sub-matrices, as specified in the research documents of the NRIET Institute.
The 10,000 T / R modules are installed on 60 submatrices of 2 meters × 7.5 meters and form a circle 30 meters in diameter. This reduces the difficulty of designing, manufacturing and above all installing the radar. The latter requires, for example, that the flatness of the sub-matrices is ≤ 3.8 mm, in accordance with the decimetric wavelength of the radar.
More than 1,000 power sources are required for proper system operation. NRIET reports indicate that the heat density of each transistor reaches "several tens of W / cm²", which requires the implementation of a large liquid cooling network.
No radar data was reported, although it can usually be as much as 4,000 km, if not more, for this type of device.
But in the simulation studies published by the Anti-Aircraft and Anti-missile Defense Academy, an institution that trains specialized officers of the Chinese Air Force is the most effective 2,000 km which is referred to as the Ground Based Radar (Band P), coupled with 800 to 3,500 km of trans-horizon radars (OTHR) and 1,000 km of X-band fire GBR-X).
The aim of the set is to detect, track, identify and then provide targeted firing solutions (missile heads in general) of a RES of 0.2 m² from the Guam area in the Pacific Ocean .
Given that China already has , and that the GBR-P is now in place, there is every indication that the construction of the last missile link to the Pacific, the GBR-X, already in progress.
The satellite image of the Chinese early warning radar in Shangdong
Diagram taken from another university document showing the operation of ABM radars
The supposed coverage of Chinese radar
It should be noted that the shape of the "modules" of this Chinese early warning radar seems to be very similar to that of the JY-26 , a three-dimensional surveillance radar operating in P-band and designed by Institute No. 38 of the CETC group.
The round "lid" of JY-26 is not a T / R module but serves to protect the dipoles underneath and also to facilitate air cooling.
These dipoles forming a cross are capable of emitting right-handed, left-handed or directional polarized waves, which improves the detection of targets with low observability, according to the manufacturer.
At the Zhuhai Air Show, technical experts from CETC, the parent company of NRIET, also indicated that the Chinese version of JY-26 deployed in Shandong, with double the modules and 4 times more power (> 100 kW) compared to the export version, has already followed the movement of the American F-22 flying over the Korean Peninsula.
To be continued.
Henri K.
Last edited:
Hendrik_2000
Lieutenant General
(cont)
hese dipoles forming a cross are capable of emitting right-handed, left-handed or directional polarized waves, which improves the detection of targets with low observability, according to the manufacturer.
The Chinese Early Warning Radar Description Panel (Image: CCTV-13)
The surveillance radar JY-26, also operating in P-band (Photo: 机 贩子)
A close-up on the antennas of JY-26 (Photo: 中华 - 暖风)
At the Zhuhai Air Show, technical experts from CETC, the parent company of NRIET, also indicated that the Chinese version of JY-26 deployed in Shandong, with double the modules and 4 times more power (> 100 kW) compared to the export version, has already followed the movement of the American F-22 flying over the Korean Peninsula.
hese dipoles forming a cross are capable of emitting right-handed, left-handed or directional polarized waves, which improves the detection of targets with low observability, according to the manufacturer.
The Chinese Early Warning Radar Description Panel (Image: CCTV-13)
The surveillance radar JY-26, also operating in P-band (Photo: 机 贩子)
A close-up on the antennas of JY-26 (Photo: 中华 - 暖风)
At the Zhuhai Air Show, technical experts from CETC, the parent company of NRIET, also indicated that the Chinese version of JY-26 deployed in Shandong, with double the modules and 4 times more power (> 100 kW) compared to the export version, has already followed the movement of the American F-22 flying over the Korean Peninsula.
Hendrik_2000
Lieutenant General
Now this is interesting apparently the US is using A1 to find missile site I have no doubt that China is using the same A1 to find AC
With commercial satellite imagery, computer learns to quickly find missile sites in China
by — October 19, 2017
Researchers use machine learning to search for SAM sites over a large search area in southeast China. (Center for Geospatial Intelligence)
Deep machine learning algorithms can help government agencies analyze satellite imagery.
WASHINGTON — For all the hype and promise around artificial intelligence and machine learning technologies in military applications, it always comes down to what specifically can be done with it.
The industry keeps rolling out new gee-whiz artificial intelligence tools but the defense and intelligence communities still are trying to figure out how to use them and whether they really work as promised.
According to a new study, there is one area where deep machine learning algorithms can definitely help the government, and that is to analyze satellite imagery.
Officials from the National Geospatial Intelligence Agency have called on the private sector to bring forth machine learning tools to automate repetitive and time-consuming image analysis tasks. They want to free up skilled analysts to spend more time on hard intelligence problems that can’t be turned over to a computer.
Researchers from the Center for Geospatial Intelligence at the University of Missouri used a deep learning neural network to assist human analysts in visual searches for surface-to-air missile sites over a large area in southeastern China. The results showed that the computer performed an average search time of only 42 minutes for an area of approximately 90,000 square kilometers. By comparison, North Korea is about 120,000 square kilometers.
“This was more than 80 times more efficient than a traditional human visual search,” the center’s director and University of Missouri electrical engineering and computer science professor Curt Davis told SpaceNews.
The software achieved the same overall statistical accuracy as human analysts — 90 percent — for correctly locating the missile sites.
“I’ve been doing this research for almost 20 years, and I do believe the application of deep machine learning technology to satellite imagery reconnaissance is revolutionary,” he said. “I never expected this type of performance that we’ve been able to see both in the lab and the study. The metrics we’re seeing, the applications to larger-scale data sets to me is revolutionary.”
Historically, machine learning algorithms haven’t performed well when they have been applied to large satellite imagery data sets, he said. The breakthroughs came in the last couple of years. The computer used in the study searched the 90,000 square kilometer area in less than an hour.
Information overload
U.S. defense and intelligence agencies are drowning in high-resolution imagery they need to analyze every day to monitor events unfolding around the world. “There is simply not enough manpower to effectively analyze all the image data collected today, and the problem is only getting worse,” Davis said.
And the technology is only going to get better, he said. “The ultimate goal is to recognize dozens and hundreds of different types of objects very quickly,” said Davis. “I believe that goal is achievable in the near future.” Researchers will be training networks to search for things military analysts typically look for, including bunkers, aircraft shelters, radar sites, antennas, satellite dishes, launch pads and tank formations.
The study used commercially available remote sensing satellite imagery of one-meter resolution. With new generations of satellites soon to be launched by commercial firms, including some with sub-meter resolution, the data deluge will continue. “It has taken a while for the remote sensing community to evaluate these deep machine learning methods,” said Davis. “Most of the studies I’ve seen were only experiments against limited data sets,” he continued. “Now we’ve been able to apply deep learning models to a large data set.”
The research was published in the SPIE Journal of Applied Remote Sensing in a special issue on deep learning in remote sensing applications. Readers can search for Chinese surface-to-air missile sites on a demonstration website that uses the same high-resolution satellite imagery and deep learning algorithms used in the study.
If and when these tools start replacing human analysts remains to be seen. National Geospatial-Intelligence Agency Director Robert Cardillo said recently he wants to automate 75 percent of the repetitive tasks analysts perform so they can focus on the “25 percent that require the most attention.”
Deep learning methods can help do that, said Davis. The tough threat posed by North Korea is a case in point. The computer can find most of the fixed-site missiles but it takes human skills to track Pyongyang’s notoriously elusive mobile ballistic missile launchers. “That’s a harder problem. They can be hiding in a cave, pop out and launch a test missile.”
Pentagon interest
The Pentagon years ago identified machine learning and artificial intelligence as central elements to the military’s modernization strategy for weapons and information systems. Clearly the industry is progressing quickly, but the Defense Department has not moved as fast in applying the technology.
“One of the challenges DoD faces in this area is that we are too often in this position where we discuss something in an abstract or theoretical way,” said Shawn Steene, senior force planner for emerging technologies at the Defense Department. He spoke Oct. 19 at a CNA panel discussion on artificial intelligence.
In recognition of the growing role of these technologies in defense, CNA, a federally funded nonprofit think tank in Arlington, Va., announced the opening of a “Center for Artificial Intelligence and Autonomy.”
“To some degree we’re limited by our creativity in the application of these capabilities,” Steene said.
He recalled when the U.S. Geospatial Intelligence Foundation put out an open-source challenge offering a prize to whoever would come up with the best algorithms to take overhead imagery and identify the buildings in the picture. “The point was to remove from the analysts the first cut layer,” he said. “Just having that program to do that, having the machine doing the first layer, I can pass that to an analyst. And instead of spending time doing basic tasks, now they can do the ‘value added’ work.”
Using artificial intelligence for data mining also could help prioritize information so networks are not clogged by data that may not be valuable, said Steene. “Instead of needing a giant pipe, if I have some screening at the front end, I can constrain the data flow,” he said. This technology offers infinite applications but the Defense Department needs to define the problems it is trying to address and “we need to use more creativity.”
With commercial satellite imagery, computer learns to quickly find missile sites in China
by — October 19, 2017
Researchers use machine learning to search for SAM sites over a large search area in southeast China. (Center for Geospatial Intelligence)
Deep machine learning algorithms can help government agencies analyze satellite imagery.
WASHINGTON — For all the hype and promise around artificial intelligence and machine learning technologies in military applications, it always comes down to what specifically can be done with it.
The industry keeps rolling out new gee-whiz artificial intelligence tools but the defense and intelligence communities still are trying to figure out how to use them and whether they really work as promised.
According to a new study, there is one area where deep machine learning algorithms can definitely help the government, and that is to analyze satellite imagery.
Officials from the National Geospatial Intelligence Agency have called on the private sector to bring forth machine learning tools to automate repetitive and time-consuming image analysis tasks. They want to free up skilled analysts to spend more time on hard intelligence problems that can’t be turned over to a computer.
Researchers from the Center for Geospatial Intelligence at the University of Missouri used a deep learning neural network to assist human analysts in visual searches for surface-to-air missile sites over a large area in southeastern China. The results showed that the computer performed an average search time of only 42 minutes for an area of approximately 90,000 square kilometers. By comparison, North Korea is about 120,000 square kilometers.
“This was more than 80 times more efficient than a traditional human visual search,” the center’s director and University of Missouri electrical engineering and computer science professor Curt Davis told SpaceNews.
The software achieved the same overall statistical accuracy as human analysts — 90 percent — for correctly locating the missile sites.
“I’ve been doing this research for almost 20 years, and I do believe the application of deep machine learning technology to satellite imagery reconnaissance is revolutionary,” he said. “I never expected this type of performance that we’ve been able to see both in the lab and the study. The metrics we’re seeing, the applications to larger-scale data sets to me is revolutionary.”
Historically, machine learning algorithms haven’t performed well when they have been applied to large satellite imagery data sets, he said. The breakthroughs came in the last couple of years. The computer used in the study searched the 90,000 square kilometer area in less than an hour.
Information overload
U.S. defense and intelligence agencies are drowning in high-resolution imagery they need to analyze every day to monitor events unfolding around the world. “There is simply not enough manpower to effectively analyze all the image data collected today, and the problem is only getting worse,” Davis said.
And the technology is only going to get better, he said. “The ultimate goal is to recognize dozens and hundreds of different types of objects very quickly,” said Davis. “I believe that goal is achievable in the near future.” Researchers will be training networks to search for things military analysts typically look for, including bunkers, aircraft shelters, radar sites, antennas, satellite dishes, launch pads and tank formations.
The study used commercially available remote sensing satellite imagery of one-meter resolution. With new generations of satellites soon to be launched by commercial firms, including some with sub-meter resolution, the data deluge will continue. “It has taken a while for the remote sensing community to evaluate these deep machine learning methods,” said Davis. “Most of the studies I’ve seen were only experiments against limited data sets,” he continued. “Now we’ve been able to apply deep learning models to a large data set.”
The research was published in the SPIE Journal of Applied Remote Sensing in a special issue on deep learning in remote sensing applications. Readers can search for Chinese surface-to-air missile sites on a demonstration website that uses the same high-resolution satellite imagery and deep learning algorithms used in the study.
If and when these tools start replacing human analysts remains to be seen. National Geospatial-Intelligence Agency Director Robert Cardillo said recently he wants to automate 75 percent of the repetitive tasks analysts perform so they can focus on the “25 percent that require the most attention.”
Deep learning methods can help do that, said Davis. The tough threat posed by North Korea is a case in point. The computer can find most of the fixed-site missiles but it takes human skills to track Pyongyang’s notoriously elusive mobile ballistic missile launchers. “That’s a harder problem. They can be hiding in a cave, pop out and launch a test missile.”
Pentagon interest
The Pentagon years ago identified machine learning and artificial intelligence as central elements to the military’s modernization strategy for weapons and information systems. Clearly the industry is progressing quickly, but the Defense Department has not moved as fast in applying the technology.
“One of the challenges DoD faces in this area is that we are too often in this position where we discuss something in an abstract or theoretical way,” said Shawn Steene, senior force planner for emerging technologies at the Defense Department. He spoke Oct. 19 at a CNA panel discussion on artificial intelligence.
In recognition of the growing role of these technologies in defense, CNA, a federally funded nonprofit think tank in Arlington, Va., announced the opening of a “Center for Artificial Intelligence and Autonomy.”
“To some degree we’re limited by our creativity in the application of these capabilities,” Steene said.
He recalled when the U.S. Geospatial Intelligence Foundation put out an open-source challenge offering a prize to whoever would come up with the best algorithms to take overhead imagery and identify the buildings in the picture. “The point was to remove from the analysts the first cut layer,” he said. “Just having that program to do that, having the machine doing the first layer, I can pass that to an analyst. And instead of spending time doing basic tasks, now they can do the ‘value added’ work.”
Using artificial intelligence for data mining also could help prioritize information so networks are not clogged by data that may not be valuable, said Steene. “Instead of needing a giant pipe, if I have some screening at the front end, I can constrain the data flow,” he said. This technology offers infinite applications but the Defense Department needs to define the problems it is trying to address and “we need to use more creativity.”
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