The Cat Homing Infrared Laser Drone Defense (CHILD) System: A Novel Approach to Suburban Defense

Dr. David Summers1 

1 Department of Neighborhood Regulated Militias, Cranberry-Lemon University, Pittsburgh, PA, USA

Abstract

The invasion of government spy drones is one of the top security concerns of all Americans.  Even though the mainstream media wants us to believe these feathered birds are just natural creatures, more and more people are beginning to believe that they aren’t real [1]. Though these ‘bIrDs’ just seem to pop up at the most convenient times, especially when your wife gets that government job she can’t tell you anything about, few people still think they’re only harmless animals. Despite studies showing widespread government damaging the power grid en masse [2], few defenses seem to stop them. For many air defense systems, they’re too difficult to track, and even harder to defeat. In this paper, the novel Cat Homing Infrared Laser Drone Defence (CHILD) system will be designed, prototyped, and tested. The CHILD system consists of a pointer breed dog, a bird feeder, a laser guidance system, and most importantly, a junkyard cat named Bandit. The CHILD system was found to reduce the bird population by a marginally better 28% in a suburban backyard. 

Keywords: Integrated Air Defense, Birds Aren’t Real, Cat Weaponization, Man’s Best Friend, Military Working Dogs

1. Introduction

People love privacy. Sometimes they’ll do all sorts of crazy things to obtain it like switching to Duckduckgo as their search engine of choice. Unfortunately, maintaining your privacy isn’t so easy with the development of the flappy wing micro drones, also known as birds. Development of such a system is nearly impossible due to many reasons. Integrated Air Defense Systems (IADS) must have the capability to find the bird, fix to the bird, track it, target it, engage it and then assess it (F2T2EA) in a fully integrated kill chain. 

Birds provide challenges for every stage of the kill chain process. They are small and hard to find and track with an automatic system. They are swift and agile. Worst of all, they are plentiful. While a surface to air homing missile could take out each bird, it would be incredibly costly over time to the average suburban homeowner who can’t afford even one patriot missile on a typical American salary.

Attempt after attempt has shown how difficult it is to defeat these unwelcomed spies. In the CHILD system, the key was to take a lesson from James Cameron’s Avatar and defeat technology with nature. Hunting dogs, specifically pointer breeds, have a long history of finding and tracking small animals. Unfortunately for the dogs, they are not capable of engaging creatures capable of flying away. Contrary to the dogs, household cats can complete on their own the full F2T2EA process for government micro drones but are too lackadaisical to ever be reliable. By integrating these elements together, using a squirrel-bird differentiator antennae, a bird feeder, central processor, a gimbaled high powered laser pointer, they can create an effective IADS system capable of defending a suburban backyard against invasive government drones. 

CHILD System Overview
Fig 1: CHILD System Overview Noah Wulf, CC BY-SA 4.0, via Wikimedia Commons Princess Pleple2000, CC BY-SA 3.0, via Wikimedia Commons Ildar Sagdejev (Specious), CC BY-SA 4.0, via Wikimedia Commons

1.1 Background

Since the 50’s the CIA has been experimenting with flappy bird surveillance micro drone technology to keep an eye on communist sympathizers. Despite the government’s effort to scrub through the historical narrative and create a convenient fiction that birds are just animals in the 1980s, the Birds aren’t Real movement realized the truth and quickly began waking up the sheeple. Regardless of the successful #BirdsArentReal campaign, not many systems have been created to stop this invasive artificial part of the new modern environment. 

In the late aughties, initial counter drone IADS prototypes were tried and tested to no avail. Some strange electro-magnetic emitters were attempted only to reveal that the birds have been hardened [3]. Next Bright lights, magnetic generators, and noises were used to confuse the birds’ sensors which only unleashed the full power of homeowner’s associations which are often used to trounce on the freedom of the common man [4]. Outside of buying neighborhood children pellet guns and letting them have target practice, not much was able to be done. While effective, a new study revealed that it could only defend against 20% of all government drones and could only be implemented when there were children with mom’s cool enough to let them play with air rifles in a stranger’s backyard [9]. This is why these children had to be replaced with the CHILD system.  

1.2 Purpose

About a year ago, my wife Gabi thinks she saw me cheating on her with another woman while she was collecting data with some Synthetic Aperture Radars [5]. While there is plenty of reason to develop such an IADS system against these drones for the common man, I need it soon. Gabi just got a job at some government institution that she can’t tell me anything about and I have noticed way more birds conveniently showing up as soon as she leaves for work. I didn’t cheat on her, it wasn’t what it looked like, and I won’t cheat on her. Ever. But I need some me time. I hope that this system will allow others to maintain privacy whether they need it or not, and in case any of their untrusting significant others begin working at a three-letter intelligence agency. 

2. System Design

As shown in figure 1, the main architecture of the CHILD system is elegant and easy to comprehend in its electronic Flintstones like design. First, the dog is deployed to point the squirrel-bird electronic differentiator antennae at small animals. Next the antennae determines if a government drone is present and uploads detection and tracking data to a central computer. Using the range and azimuth from the dog backpack antennae contraption, a track is then fed to a gimballed laser pointer which alerts a vicious interceptor cat and guides their predator eyes to the vulnerable bird. Once the cat does its thing, it retrieves the bird and deposits it at our backyard door in a pile so that Gabi can see what happens when she tries to spy on me during the day for the final assessment stage of the F2T2EA process. 

2.1 Pointer Dog Detection Device

Animals have long been bred to assist humans in the hunt. Dogs particularly have evolved through different breeds to specialize in different tasks whether it’s hunting, shepherding, or attracting single ladies at the park. If these drones were ground based there would be a breed for that. But they’re not. In a fascinating study by [6] dogs’ bread to point at small game have been shown to also point at these small government micro drones. While the dogs have no capability to range or accurately point to the drone, or filter their measurements with a Kalman filter into useful tracks, they have been shown in [6] to point with under 5 degrees of accuracy in azimuth and 10 degrees elevation. 

2.2 Bird Feeder draw

While the CHILD system is effective at completing a full F2T2EA kill chain, the map of effective coverage is typically not extensive. With as many birds as they are using to spy on me every day, the CHILD system has the best kill rate when birds are funneled into a vulnerable area. 

CHILD Effectiveness Zones
Figure 2: CHILD Effectiveness Zones MJ Boswell from Annapolis, Md, USA, CC BY 2.0, via Wikimedia Commons

When the public began to question what these ‘natural’ birds even ate if they weren’t powered by low voltage wires [2], the paid government scientists in the 1990s came up with the flimsy excuse of seeds. Through this marketing campaign, every bird model was then trained to ingest bird seeds from marketed bird feeders. This allowed the birds to not only seem more lifelike but also encourage unknowing civilians to buy such products and attract the drones right to where they can get the best vantage point on their personal lives. Sinister!

While the blue pilled may use this feature to their disadvantage, the CHILD system exploits it. By attracting all backyard birds to a central, seemingly safe bird feeder, they fall right into the pointer dog’s favorite napping spot and low enough for pouncing range of the interceptor. 

2.3 Drone-Squirrel Electronic Differentiator

The biggest issue with the pointer dog detection and direction-finding stage of the CHILD system is that most pointer dogs point at all small animals and not just birds. In order to close this functional gap, every pointer dog in the CHILD system was outfitted with a backpack containing a separate ranging and direction-finding antenna integrated with a full IMU-GPS to fuse the raw pointer-dog/antennae data into new drone tracks. These tracks are then uploaded to a central computer for further cat interceptor tasking.   

In addition to directional accuracy and ranging, the antennae can detect 5G radio waves specific to government drones and non-existent in the majority of the known squirrels and other small woodland critters with the exception of the hipster rats living in Portland [7]. This filter greatly reduces nuisance alarms which take up valuable cat tasking time. 

2.4 Laser Guidance System

Once a bird is confirmed as a bird by the CHILD central computer, a series of gimbaled high powered green laser pins will begin guiding the cat interceptor to its intended target. While they aren’t specifically infrared lasers, we needed an ‘I’ to make the CHILD acronym catchier. 

2.5 Cat Hunter Seeker

The most crucial and task saturated portion of any bird defense IADS is always the engagement device. To the detriment of the governmental spy-drone program, common house-cats are the leading cause of bird destruction in most suburban neighborhoods [8]. In the quest to make the birds look natural, they began to look like prey. 

Unattended outside, these cats may take out many of these pesky drones but rarely in a concentrated area or in a timely manner. There are too many birds flying around for cats to get every single one. It is however possible if tasked correctly in the CHILD kill chain. Once guided to the intended target, preferably near the bird feeder for rapid and unexpected attack, the cat hunter seekers can jump meters into the air catching the low flying drones. 

3. Prototype Construction

Gathering up all of the raspberry pi’s from all of my unfinished projects, a prototype was easily made with no extra hardware cost. Linking through my house’s wifi network, a command and control infrastructure was able to fuse tracks from the dog detection device into the cat guidance system easily in a functional Plus Plus Plus framework. 

3.1 Dog Antennae Cyborg Implementation

After a careful selection process shown in Appendix A, the pointer dog princess was chosen to be integrated in the first prototype. Out of all of the dogs, she was the only one that was able to reliably point, stay vigilant, and didn’t fight us when we tried to put the antenna backpack on. 

An image of Princess with the full system backpack on can be seen in figure 3. The backpack includes the bird finding antenna, a uplink module, and a GPS, all integrated into a Pixhawk. Foam padding was used for Princess’s comfort. 

Princess with Drone-Squirrel Differentiator Princess
Fig 3: Princess with Drone-Squirrel Differentiator Princess Pleple2000, CC BY-SA 3.0, via Wikimedia Commons

When the system successfully detects a full kill from CHILD, the dog is released from the pointing position with a ding and a small treat is released as a behavior reinforcement reward.

3.2 Laser Guidance System

As shown below in Figure 4, there are too many corners and turns for only one laser guidance system to direct the cat interceptor. Through the network of gimbaled laser pointers, each zone could be covered in the automated guidance system.

Sun Spot to Kill Zone Laser Guidance Network
Figure 4: Sun Spot to Kill Zone Laser Guidance Network MJ Boswell from Annapolis, Md, USA, CC BY 2.0, via Wikimedia Commons

While a machine learning computer vision scheme was intended to direct the lasers, we couldn’t get the system working in real time and barely got the vision aided system to recognize the difference between a cat and a dog based solely on the database of images we captured last Wednesday. Instead, multiple trial runs were used to adjust the speed of the laser pass off system to ensure the hunter-seeker doesn’t get lost chasing the laser while maintaining a fast enough speed to maintain the cat’s murderous attention.

3.3 Cat Interceptor Implementation

Finally, the neighborhood stray cat Bandit was chosen through a lengthy and extensive selection process detailed in Appendix B. The gray tabby Bandit outperformed the other cats by jumping the highest, sprinting across the room the fastest, and by showing the most appropriate level of aggression compared with other vicious felines considered for the CHILD prototype.

Before completing any test with Bandit in the fully integrated system, one final safety issue needed to be addressed. The high-powered green laser was determined to be too bright for Bandits’ eyes over repeated exposure. Because Bandit would be exposed to the bright light multiple times a day, a set of safety goggles were required to be worn at all times while the system is operational. 

Figure 5: Bandit Ruggedized against Laser Eye Damage 
Figure 5: Bandit Ruggedized against Laser Eye Damage 

4. Results

The CHILD system was tested over two weeks while my wife was away at work. During this time, I automated my day job and kept careful notes of the number of birds killed or scared off by the system as well as intermediary steps to address problems such as the laser not correctly guiding Bandit or the dog cyborg detecting false alarms in the system. Unfortunately, I wasn’t able to babysit the system the entire time and programmed the CHILD core processor to log its tracks. Likewise, dead birds at my back door would prove to be positive proof of CHILD’s effectiveness.

4.1 CHILD Performance

The CHILD system was marginally better than children with pellet guns at an effectiveness of 28%. The CHILD system destroyed a total of 133 drones. The total number of drones is a guess based on the previous pellet gun research when I was taking more detailed notes [9] because after we started the test we realized we didn’t have any bird truth data. Results of the effectiveness at each step in the kill chain can be seen in table 1 below. 

AttemptsSuccessesPercent
DetectN/A4072N/A
TrackN/A813N/A
Laser Guidance76331240.9%
Engage29713344.8%
Assess1336951.9%
Table 1: CHILD Kill Chain Performance

Each step of the kill chain succeeded about half of the time at each step. While this appears to be particularly low, if each spy drone is a repeat offender it might be enough over time to clear an area of birds. It is also important to mention that among the kill chain steps, sometimes the CHILD system was not able to proceed. This was primarily due to Princess scaring off the drone before Bandit could get to the bird feeder or the system getting hung up on one of the steps. For instance, towards the end of the day, Bandit started to get bored chasing the green laser and it took a while to stalk the dot and then the bird. 

Unfortunately, without any bird truth data, it became impossible to evaluate Princess’s performance or the accuracy of the Antennae detection and ranging device. In test with a captured bird, we did measure that the antenna direction finding was on average less accurate than Princess by 3 degrees, but with two meters of accuracy in range finding.  

Without any additional cat training, Bandit did manage to pile up 69 of the birds on our backyard door while the remaining 64 were found scattered about the yard in a pile of feathers. 

4.2 System Deficiencies

This is only the first iteration of the CHILD system and after changing our expectation of the performance we were happy with the results. There were many problems found in the period of testing and evaluation, but none that broke the entire IADS. 

Princesses performance was perfect. She was the best dog. Her antenna however struggled. In between cell phone signals, and other interference, the antenna began overtasking Bandit throughout the day. Many times a track would be developed on a squirrel by mistake which would only last a few seconds. By the time a real bird showed up, Bandit didn’t bother moving. 

Bandit and the laser guided system did present problems as well. Many times, the laser guidance system would move too slowly and the laser dot would appear on Bandit’s paw confusing him until he ignored the moving laser or missed a pass off around the corner before going back to lay down in the sun.  Additionally, many times, Bandit would take too long to get to the bird by stalking far too slowly. In the next iteration of the CHILD system, multiple cat interceptors should be used to adequately eliminate all backyard drones. 

Finally, Bandit appeared to have a serious reliability issue which requires regular maintenance of the CHILD system. He kept getting stuck in trees going after the birds. The CHILD system would then alert me to go rescue Bandit from a high branch. There appears to be no permanent solution to this reliability issue. 

5. Conclusion

The war against the birds has just begun and we have our first working prototype. China tried to fight them during the four pests campaign and failed. The CHILD system, though it is in need of more development, shows promise. With high powered blinding lasers and more technology-animal integration across the backyards of America, it could soon be too costly for the government to spy on us with these birds. Start training your dogs to point and your cats to kill and chase dots, they may soon be part of the solution to take back our privacy!

6. Conflicts of Interest

I’ve always thought that Princess was the best girl. 

7. References

  1. https://birdsarentreal.com/
  2. Powers D. 2020 Adaptive Smart Grids for Migratory Government Drones :: Journal of Astrological Big Data Ecology
  3. Yurgertz, F. 2009 Electronic Warfare Techniques Against Birds :: Journal of the Well Regulated Militia
  4. Hanz, A. 2012 Disco is Back: Fight Government Drones with a Light Show :: Journal of the Boogie Woogie Defense
  5. Summers, G. 2020 Limitations in Aerial SAR Imagery for Agriculture and Modern Relationships :: Journal of Astrological Big Data Ecology
  6. Caesar D. 2017 Mans Best Friend: A K9 Defense against Government Spy Birds :: Annals of Dog Weaponization
  7. Portlandia Rats https://www.youtube.com/watch?v=y-qjnzqnqKM
  8. Krazy C. L. 2019 Cat Hunter Seekers: Weaponizing Cats for your Personal Privacy :: Journal of Crazy Cat Ladies
  9. Summers D. 2020 Culling the Government Bird Spy Population with the Proliferation of Air Rifles :: Journal of a Well Regulated Elementary School

 Appendix A: Dog Selection

After the animal shelter turned me down when I asked to run experiments for science, I had to turn to my neighbors. Among those dogs were my best friend’s wife’s dog Major, a DINC couple’s two dogs Niles and Frasier, and my dog Princess. Images of the test dogs can be seen in Figures 6-9. 

The dogs were tested across four tests, Pointing Holding Time, Detection Time, Uptime Under Weight, and Pointing Accuracy. In the Pointing Holding time, we measured how long a dog could hold a pointing position to a bird. Likewise we measured how long it took the dog to point to the bird once revealed. During the pointing tests, we measured how accurate their pointing angle was for the best passoff to the laser guidance system. Finally, we measured how long each dog would remain standing with the full Squirrel-Bird Electronic Differentiator contraption before sitting down. The results are shown in Table 2.

Pointing Hold TimeDetection TimeUptime Under WeightPointing Accuracy
Major5s10s44m11 deg
Frasier3s15s1Hr 12m23 deg
NilesN/AN/A0.3sN/A
Princess82s3s7Hr 38m5 deg
Table 2: Dog Selection Results

As shown in the table of results, Princess was the clear winner. Though Major and Frasier were able to complete the task, they would not have the endurance to protect a home over an entire day as the initial prototype would require. Niles couldn’t do anything, He couldn’t lift the antenna contraption and he couldn’t even point or detect any birds whatsoever. All he did was just sit down breathing heavily, making everyone uncomfortable. 

Fig 6: Major
Fig 7: Frasier
Fig 8: Niles
Fig 9: Princess Pleple2000, CC BY-SA 3.0, via Wikimedia Commons

 Appendix B: Cat Selection

The shelter wouldn’t let us test cats either and that probably saved us some time because the ones we found and knew were hard to control and test. Among the cats that came back to us when we started leaving food out at our front door was Pumpkin, Cleopatra, and Bandit.

The metrics used to assess the feline candidates as a CHILD hunter-seeker interceptor was stalking time, Jump Height, 10 Yard Sprint Time and a group scored metric ferocity. The results for each cat can be seen in Table 3. 

Stalking TimeJump Height10 Yard SprintFerocity
Pumpkin5s0.7m24s8
Cleopatra17s1.8m5s4
Bandit14s2.3m3s6
Table 3: Cat Selection Results

As shown in table 3, the results were a little bit more mixed. While Pumpkin was clearly the least athletic, he was the most ferocious. Meanwhile Bandit appeared to be the best fit in between run time, jump height and medium ferocity and stalking time. While it may be better to stalk a bird a little faster, if the cat interceptor stalks too fast, it may decrease the kill rate by spooking the bird spies. We noticed this occurrence several times during Pumpkins test who just went for it. It turns out that in a cat interceptor, there may be too much ferocity. 

Fig 10: Pumpkin
Fig 11: Cleopatra
Fig 12: Bandit

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Published by B McGraw

B McGraw has lived a long and successful professional life as a software developer and researcher. After completing his BS in spaghetti coding at the department of the dark arts at Cranberry Lemon in 2005 he wasted no time in getting a masters in debugging by print statement in 2008 and obtaining his PhD with research in screwing up repos on Github in 2014. That's when he could finally get paid. In 2018 B McGraw finally made the big step of defaulting on his student loans and began advancing his career by adding his name on other people's research papers after finding one grammatical mistake in the Peer Review process.

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