5 ms·

Almost certainly. But they can't keep track accurately and the location of the aircraft is not accurate. The inaccuracy can be several km. Stealth is still 80%

Almost certainly. But they can't keep track accurately and the location of the aircraft is not accurate. The inaccuracy can be several km. Stealth is still 80% of shaping. Specular reflection can be reflected away from the radar receiver. In the resonant scattering region, where the signal amplitude matches the object sizes, you remove radar return by removing all parts that are a similar size to the wavelength, like the tail. Coatings and Absorbers reduce radar even return more but only after the shaping works. If you can get radar into an angle that the shape was designed for, or transceiver and receiver are in separate locations stealth advantage decreases dramatically. Chinese are probably the first to deploy long-range air-to-air missiles that have dual sensors. Both radar and IR. (Stunner missile has that already, but it's ground-to-air missile). Traditionally IR is used only in short-range missiles. You direct the missile to approximate position and then it uses IR and radar together to remove stealth.

sandworm101 5y ago
>> and then it uses IR and radar together to remove stealth. So what happens when the dual seekers give different results? If there were three seekers then you could ignore one, but with only two you cannot check one against another. What if the radar says turn left but the IR says turn right? Having two seekers may make the target's life easier: defeat either seeker and you defeat both.
- nradov 5y ago
  It's like any other sensor fusion problem. You take a weighted average of the detected target bearing based on whatever data you have. Even if the target manages to completely "defeat" one sensor by somehow becoming invisible it doesn't mean that sensor will report a totally spurious bearing; you just won't get any meaningful data at all from it and thus ignore it.
  - sandworm101 5y ago
    Left + Right /2 = Strait = Miss. Small errors count. A few degrees off and your missile doesn't get to the target. Any averaging will probably result in a miss. In such cases a single sensor would be better, or two different sensors on two different missiles. This comes up in all manner of flight systems. Take altitude. If one sensor says you are at 1000feet and another says 10,000, the one thing everyone should agree is that you aren't at 5500. One of the sensors is wrong and needs to be ignored, but how do you pick between the two?
    - nradov 5y ago
      That's not how modern sensor fusion algorithms work. It's never a simple average calculation. The inputs from various sensors are weighted based on confidence levels. In extreme cases sensors reporting bad or inconsistent data are ignored.
    - travisjungroth 5y ago
      > One of the sensors is wrong and needs to be ignored, but how do you pick between the two? What did the sensors say one minute ago? There's no reason this has to be Markovian.
      - sandworm101 5y ago
        Because, in a jamming/deception scenario, the jammer acting on a sensor won't just introduce a false reading. It will gradually transition from a true to false state in a manner that looks natural. The jammer will attempt to capture the sensor's attention and then shift its attention away from its target ("seduction"). In such cases it is very difficult/impossible to tell which is true based on past readings from the sensor. Google jamming and "capturing the gate" or "doppler pull", techniques specifically to defeat countermeasures dependent on past readings. With two sensors against a jamming target, the sensor with the clearest signal/most confidence is probably the one being most jammed. (IR flares do similar things too.)
    - robotresearcher 5y ago
      The parent said weighted average. The weight can be picked cleverly: it does not have to be the 0.5 of your example, and it doesn’t have to be constant. For example, the Kalman Filter tells you the weight to apply to each new sample and the last estimate to make a new estimate. These weights are optimal if the measurement errors have a Gaussian distribution with zero mean. In many practical systems they are usably good even when that assumption does not perfectly hold. In your example the new measurement that was less consistent with the last fused estimate would be downweighted by a KF.
      - sandworm101 5y ago
- krona 5y ago
  The Kalman filter is but one example of estimating unknown variable (the target location, heading, speed) using a joint probability distribution of multiple sensor inputs with different characteristics.
jandrewrogers 5y ago
The launch platforms can feed the necessary positional data to the missile, which can switch to IR search mode as it approaches the area of the target. Most newer US platforms use a mix of inertial and IR imaging guidance. Even the longer range radar-guided missiles typically don't turn on their radar until they are relatively close to the target; effective long-range radar has power requirements that don't fit in a missile very well. The dual-mode terminal guidance on the Chinese missile may be a response to the fact that the US has very good countermeasures for IR terminal guidance. IR guidance is cheap but it may not be reliable against some advanced targets.
- p_l 5y ago
  Or it could be something they picked up from Soviet defense forces, where the doctrine was to fire long range missiles in pairs - first an IR seeker then radar one p
- angry_octet 5y ago
  The diameter of the missile also imposes significant limitations on the RADAR. IR sensors couldn't be in the nose cone, it's hard to see them being very sensitive or capable against active decoys. In contrast, the AIM-120D has bidirectional data link, so it can feed it's RADAR picture back to the launch platform.
  - jasonwatkinspdx 5y ago
    My understanding is multi mode seekers use a simple trick where they have a Gregorian telescope where the mirrors do double duty for both RF and IR. This allows simultaneous radar, IR, and laser seeking in one unit.
AtlasBarfed 5y ago
With CPU and sensors getting so cheap, you'd think AI missile targeting would be taking off. IR+Radar seems like such a basic early-2000s strategy given how shockingly cheap everything has gotten. The fact that Radar + IR is a spoken of as somewhat novel either tells me the defense industry parasites are way behind or the public intel is just several decades behind. But given the speeds I can see the problem being more difficult that I think.

sandworm101 5y ago

>> and then it uses IR and radar together to remove stealth. So what happens when the dual seekers give different results? If there were three seekers then you could ignore one, but with only two you cannot check one against another. What if the radar says turn left but the IR says turn right? Having two seekers may make the target's life easier: defeat either seeker and you defeat both.

nradov 5y ago
It's like any other sensor fusion problem. You take a weighted average of the detected target bearing based on whatever data you have. Even if the target manages to completely "defeat" one sensor by somehow becoming invisible it doesn't mean that sensor will report a totally spurious bearing; you just won't get any meaningful data at all from it and thus ignore it.
- sandworm101 5y ago
  Left + Right /2 = Strait = Miss. Small errors count. A few degrees off and your missile doesn't get to the target. Any averaging will probably result in a miss. In such cases a single sensor would be better, or two different sensors on two different missiles. This comes up in all manner of flight systems. Take altitude. If one sensor says you are at 1000feet and another says 10,000, the one thing everyone should agree is that you aren't at 5500. One of the sensors is wrong and needs to be ignored, but how do you pick between the two?
  - nradov 5y ago
    That's not how modern sensor fusion algorithms work. It's never a simple average calculation. The inputs from various sensors are weighted based on confidence levels. In extreme cases sensors reporting bad or inconsistent data are ignored.
  - travisjungroth 5y ago
    > One of the sensors is wrong and needs to be ignored, but how do you pick between the two? What did the sensors say one minute ago? There's no reason this has to be Markovian.
    - sandworm101 5y ago
      Because, in a jamming/deception scenario, the jammer acting on a sensor won't just introduce a false reading. It will gradually transition from a true to false state in a manner that looks natural. The jammer will attempt to capture the sensor's attention and then shift its attention away from its target ("seduction"). In such cases it is very difficult/impossible to tell which is true based on past readings from the sensor. Google jamming and "capturing the gate" or "doppler pull", techniques specifically to defeat countermeasures dependent on past readings. With two sensors against a jamming target, the sensor with the clearest signal/most confidence is probably the one being most jammed. (IR flares do similar things too.)
  - robotresearcher 5y ago
    The parent said weighted average. The weight can be picked cleverly: it does not have to be the 0.5 of your example, and it doesn’t have to be constant. For example, the Kalman Filter tells you the weight to apply to each new sample and the last estimate to make a new estimate. These weights are optimal if the measurement errors have a Gaussian distribution with zero mean. In many practical systems they are usably good even when that assumption does not perfectly hold. In your example the new measurement that was less consistent with the last fused estimate would be downweighted by a KF.
    - sandworm101 5y ago
krona 5y ago
The Kalman filter is but one example of estimating unknown variable (the target location, heading, speed) using a joint probability distribution of multiple sensor inputs with different characteristics.

jandrewrogers 5y ago

The launch platforms can feed the necessary positional data to the missile, which can switch to IR search mode as it approaches the area of the target. Most newer US platforms use a mix of inertial and IR imaging guidance. Even the longer range radar-guided missiles typically don't turn on their radar until they are relatively close to the target; effective long-range radar has power requirements that don't fit in a missile very well. The dual-mode terminal guidance on the Chinese missile may be a response to the fact that the US has very good countermeasures for IR terminal guidance. IR guidance is cheap but it may not be reliable against some advanced targets.

p_l 5y ago
Or it could be something they picked up from Soviet defense forces, where the doctrine was to fire long range missiles in pairs - first an IR seeker then radar one p
angry_octet 5y ago
The diameter of the missile also imposes significant limitations on the RADAR. IR sensors couldn't be in the nose cone, it's hard to see them being very sensitive or capable against active decoys. In contrast, the AIM-120D has bidirectional data link, so it can feed it's RADAR picture back to the launch platform.
- jasonwatkinspdx 5y ago
  My understanding is multi mode seekers use a simple trick where they have a Gregorian telescope where the mirrors do double duty for both RF and IR. This allows simultaneous radar, IR, and laser seeking in one unit.

AtlasBarfed 5y ago

With CPU and sensors getting so cheap, you'd think AI missile targeting would be taking off. IR+Radar seems like such a basic early-2000s strategy given how shockingly cheap everything has gotten. The fact that Radar + IR is a spoken of as somewhat novel either tells me the defense industry parasites are way behind or the public intel is just several decades behind. But given the speeds I can see the problem being more difficult that I think.