Professor Michael Littman of Princeton University, who is a consultant on our Neural Space Navigator NASA Phase I SBIR, has the gimbaled camera in action! Check out the video.
The high dynamic range camera is mounted on a pan/tilt mechanism that uses stepping motors with harmonic drives. Harmonic drives have zero backlash. The camera assembly is 17 cm tall.
The Neural Space Navigator uses a neural network for terrain relative navigation during landings or takeoffs. Otherwise it uses the angles between planetary horizons or centers and stars combined with planetary chord widths for navigation measurements. The system uses an Unscented Kalman Filter and an Inertial Measurement Unit for both navigation and attitude determination. Contact us for more information!
The thesis gives an excellent overview of nuclear fusion technology and space propulsion. The author then goes on to do trajectory analysis for the Titan mission using STK. He presents three different mission strategies using Direct Fusion Drive. He includes all of the orbital maneuvering needed to get into a Titan orbit. His mission designs would get a spacecraft to Titan in two years.
Dr. Gary Pajer, Yosef Razin and Michael Paluszek of Princeton Satellite Systems and Dr. Samuel Cohen of the Princeton Plasma Physics Laboratory were awarded a 2020 Thomas Edison Patent Award for U.S. Patent 9,822,769, “Method and Apparatus to Produce High Specific Impulse and Moderate Thrust from a Fusion- Powered Rocket Engine.” This patent is for a new type of nuclear fusion reactor that is compact, making it suitable for mobile power, emergency power, space propulsion and power. The award is given by the Research and Development Council of New Jersey.
Images of a mobile version of the reactor, and a version used for a rocket engine are shown below. The work is currently funded by an ARPA-E OPEN grant. NASA has also funded this work through the NASA NIAC program.
The 41st Edison Patent Awards Ceremony, themed “Transforming Hope into Action” will take place virtually on November 12th. Contact Vanessa Johnson for more information about the event.
Spacecraft with thrusters or instruments with large magnetic dipole will experience torques in a planetary magnetic field. U.S. Patent 10,752,385, just granted to Princeton Satellite Systems, uses a current loop to cancel the magnetic field of the onboard dipole. The patent text is:
“A dipole cancellation system and method may include a plurality of magnetometers for measuring a device magnetic field associated with a plurality of device coils generating a device magnetic field having a primary magnetic dipole moment. A compensating coil carrying a compensating current running a first direction that generates a compensating magnetic field having a compensating magnetic dipole moment. The compensating coil may be positioned and the first current may be selected so that the compensating magnetic dipole moment completely cancels the primary magnetic dipole moment. A method may use the system to stabilize a spacecraft by calculating an estimated torque of the spacecraft, receiving a value for an external magnetic field, receiving a value for a device magnetic field, and calculating and applying a compensating current may be then applied to the compensating coil to cancel the primary magnetic dipole moment, wherein the spacecraft is stabilized.”
Power went down when Hurricane Isaias moved in. Fortunately our customer had a SunStation solar power system with Lithium battery backup. Unlike other solar systems, this system has a transfer switch to disconnect the solar system from the grid so that the solar power system can power the house when the grid is down. The batteries provide enough power to keep critical systems going when it is really cloudy or at night.
You can see the system in operation here. The first shows the system when the solar power is insufficient to power the house.
The following shows the system with enough solar power to charge the battery and power the house.
Even on a cloudy day, you usually get enough solar power to keep the house running. The 0.2 kW load includes lighting, refrigerator, WiFi and other loads. This system has 14.4 kWh of storage, so it could run the house, without solar, for 72 hours.
For more information check out our SunStation page.
We are pleased to share that PSS has been selected for two NASA Small Business Innovative Research (SBIR) awards. The SBIR program enables small business to engage in research or research and development funded by the federal government. The purpose of a SBIR award is to move toward commercialization of a product. It’s a great program that allows small businesses to get a product on the market without putting up as much of their own internal research and development funds.
Our first award is for a proposal called “Neural Space Navigator.” This proposal is for research that builds off of our Optical Navigation System (ONS), adding a new capability to the system: Terrain-relative navigation using neural networks. This capability comes at a critical time for NASA’s ongoing lunar exploration program, whose small Commercial Lunar Payload Services (CLPS) landers are scheduled to have their first missions in 2021. In Phase II, we would work with Lockheed Martin (LM). LM created the optical navigation system used on NASA’s OSIRIS-REx mission. Professor Michael Littman of Princeton University will be helping on this contract.
Our second award is for a proposal called “Multi-Megawatt Superconducting Motor for Electric Aircraft.” This proposal is for research toward a powerful superconducting motor for use in partially- and fully-electric aircraft. We are working with Superconducting Systems, Inc. from Massachusetts on this contract. There are some great ideas for ways to make aircraft more fuel-efficient using electric motors (see a NASA report here for some examples). This research will make lighter and higher power motors possible, powerful enough to propel large commercial aircraft, allowing some of the concepts in that report to become a reality.
This work is a spin-off of our nuclear fusion work, in particular our current NASA STTR (with PPPL) to study the effects of plasma pulses on superconducting coils.
We are very excited to be working with NASA on such interesting projects. The next step in the process is contract negotiations, in which the details of the proposed research are hammered out. If the next 6 months go well, these awards can serve as the basis for a Phase II SBIR, which awards significantly more time and resources.
Today, I will discuss two functions in release 2020.1 of the Spacecraft Control Toolbox (SCT) which can be used to get your spacecraft into a lunar orbit. They are LunarTargeting.m and LunarMissionControl.m. They are demonstrated together in the script LunarMission.m.
LunarTargeting.m produces a transfer orbit that starts at a Low Earth Orbit (LEO) altitude and ends up passing by the Moon with a specified perilune (periapsis of the Moon) and lunar orbital inclination. Its novel approach to the patched-conic-sections model of multibody orbital transfers uses the solution to Lambert’s problem to target a point on the gravitational boundary between the Earth and the Moon. Then it numerically optimizes over points on that surface until the initial velocity of the transfer is minimized. LunarTargeting.m requires the MATLAB optimization toolbox.
LunarMissionControl.m implements a control system which enables a spacecraft to propulsively enter lunar orbit. Like the other control systems implemented in the SCT, it stores its active state and degrees of freedom in a data structure, and accepts a list of commands as arguments. The commands we’ll see used here are ‘initialize,’ ‘lunar orbit insertion prepare,’ ‘align for lunar insertion,’ and ‘start main engine.’
LunarMission.m ties them both together and simulates a spacecraft, down to the attitude-control level. The simulation includes power and thermal models. The spacecraft can be controlled by reaction wheels or thrusters. Forces from the Sun, Earth, and Moon are included. The spacecraft starts on the trajectory returned by LunarTargeting.m, then acts in accordance to commands to LunarMissionControl.m. It takes the spacecraft 4.5 days to get to perilune, at which point it inserts itself into lunar orbit. Let’s take a look!
Take a look at the above figure. This is the entire mission trajectory in the Earth-Centered Inertial (ECI) frame. We can see the initial transfer orbit as the red line. Then it approaches the blue line (the Moon’s orbit), and begins corkscrewing around it after orbital insertion. Let’s look at that insertion in close-up:
The above figure shows the final part of the trajectory in Moon-centered coordinates. The red line starts as the spacecraft passes the imaginary gravitational boundary between the Earth and the Moon. It falls closer to the Moon, and at its closest point, fires its engines to reduce its velocity. You can’t see it in this figure, but that process is actually resolved on a 2 second timescale. The spacecraft is commanded to point retrograde using a PID controller, waits until it has pointed correctly, then fires its engines for a prescribed duration. If you look closely, you will see that moon has a 3 dimension surface courtesy of the Clementine mission.
Let’s finish this post off with some technical details:
On the far left, you can see the reaction wheel rates. They stay at zero for 4.5 days, as the spacecraft coasts. Then, when the craft is commanded to point retrograde for its orbital insertion, you can see wheels 2 and 3 spin up. Wheel 1 stays near zero; its vertical scale is 10^-16. Then in the center, you can see fuel use. The only fuel use is the insertion burn, so fuel stays constant until 4.5 days in. Less than 2 kg of fuel is used for this example, as the spacecraft is a 6U cubesat. On the right, the components of the body quaternion are displayed. Again, they are constant until 4.5 days in, when the craft is commanded to point retrograde.
I hope you’ve enjoyed this demonstration of how to simulate a lunar mission with the SCT! For more information on our toolboxes check out our Spacecraft Control Toolbox for MATLAB. You can contact us directly by email if you have any questions.
Princeton Satellite Systems has been in a leader in renewable energy with its SunStation home solar power system with battery backup. We introduced this product back in 2013. SunStation has lithium-ion phosphate batteries, the most stable and reliable batteries for home use. The core of the system is the Outback Inverter that seamlessly switches from grid power to internal power.
The solar system in the installation produces 7.3 kW of power, much more than the house needed for electric power including charging a Nissan Leaf and Toyota Prius Prime. The heating and air conditioning system was nearing its end-of-life so we decided to replace it with a geothermal heat pump. A heat pump is essentially an air conditioner that can both reject heat to a source and absorb heat from a source. The problem with both is that when the outside temperature is high, for rejecting heat, and low, for absorbing heat, the system loses efficiency. Modern air-source heat pumps are very efficient but do need backup resistance heating in some climates.
A ground source heat pump, or geothermal heat pump, uses the ground as the medium for absorbing or rejecting heat. The option we chose, due to land constraints, is to have two wells several hundred feet deep as the source. Alternatives are trenching, or a pond if you have one in your yard. The ground is always at around 50 deg F. The system was sized so that it rarely, if ever, needs resistance heating.
The geothermal system, which is made by WaterFurnace, was installed by Princeton Air. No changes to the SunStation were needed. The core geothermal system is shown below. The valves to the ground loops are in the foreground and the geothermal system is on the left.
The lines that run to the outside ground loops are shown below.
The system has a preheater for the (still gas) hot water heater. The gas water heater was less than a year old, so it didn’t make sense to replace it. The preheater is an electric hot water heater that does not have the heating coils connected.
The SunStation is shown below. The Outback inverter is on the bottom left. The boxes on top provide arc protection, which is now included in the inverter. The batteries on on the right and the battery management electronics between the inverter and the battery cabinet.
The well digging was quite a project. This picture shows the drilling rig.
This second picture shows the yard after the drilling was complete. Drilling took three days total.
The following system shows the SunStation with geothermal in operation. The Prius Prime is charging which is most of the load. The system is still sending considerable power to the grid. On average the house powers itself and two other houses.
Geothermal, with solar and battery backup is the ideal solution for new homes and for renovations to existing homes. There is no reason to even have a gas hookup anymore. Contact us at SunStation for more information
Not all the new functions in 2020.1 are specific to spacecraft. We have also been hard at work adding new functionality to the core toolbox. Here, I’d like to give an example of one of our new functions for performing a Wavelet analysis.
But what is a Wavelet analysis? Well, you plot the Wavelet transform of a signal when you want to visualize how the frequency spectrum changes in time. The Wavelet transform is a lot like a Fourier transform that you perform at every possible starting point, with an appropriate window function multiplied in so that you’re only looking at a portion of the signal.
But there’s one added wrinkle, because the frequency spectrum at a specific frequency at a specific time doesn’t technically exist. It’s not technically possible to know what the component of a signal at 100 kHz is at 0.5 seconds in, because the frequency spectrum depends on the entire signal. There has to be some trade-off between time resolution and signal resolution. If we look at a very long chunk of the signal, we can nail down its frequency components very well but we can’t see them change quickly. If we look at a very short chunk of the signal, we know precisely when the frequency changes but we can’t tell the difference between two similar frequencies. It’s a trade-off.
Now let’s get to the examples! The new function in 2020.1 is called WaveletMorlet because the specific window function we use is called the Morlet wavelet (A Wavelet transform using a Morlet wavelet is also called a Gabor transform). Here’s the signal that we’ll be analyzing:
We already know what we’re going to expect in this example. It looks like there’s a persistent, low-frequency component, then a higher-frequency component whose frequency goes up, peaks around 0.25 seconds, then goes down, and bottoms around 0.75 seconds. Here’s what the Wavelet transform looks like:
Great! Exactly what we expected. This was a simple case, but you can imagine how this analysis would be useful if there were a greater spread in frequencies, a longer signal, or both.
Now, let’s explore that trade-off that I mentioned earlier. What does the signal look like when you choose a different value on that trade-off? For the above analysis, I kept the default wavelet width parameter of 10. Here’s what it looks like when we prioritize time resolution over frequency resolution by choosing 5, then frequency resolution over time by choosing 25:
For a wavelet width parameter of 5, all that happens is that the signal gets broader in the frequency direction. For 25, what’s happening here? Sure, at 0.25 seconds it appears that the visualization is able to nail down the frequency to a tighter band, but what’s happening to the rest of the image? The answer is that the frequency is changing too fast for this chosen time resolution. The signal doesn’t spend long enough at any given frequency for the algorithm to identify a significant component there.
Thanks, all, for tuning in to this update from PSS, and thanks for this opportunity to get into the nitty gritty of one of our new mathematics functions!
A popular way of launching a small satellite is to bring it up on an International Space Station resupply mission. The Spacecraft Control Toolbox has functions to help you animate the orbit of your spacecraft near the ISS. A function, ISSOrbit, generates the orbital elements for the ISS. ISSOrbit generates Keplerian Elements from the latest 2-line elements. We use the function CoplanarOrbit to create an orbit 50 m below the ISS. There are no disturbances and the gravity model is for a point mass Earth.
DrawSpacecraft.m is a function that will draw any number of spacecraft in the viewer. This is the ISS and our, very small, NanoSatellite. The MATLAB camera controls allow you to zoom in or rotate the view. The view is with respect to the first satellite entered in the argument list, which in this case is the nano satellite.
DrawSpacecraft also does animation and will create an avi file. You can see the animation on our YouTube Channel or by clicking the video below. We converted the avi file to an mp4 file using a movie converter.
The script is an m-file that you can download, just to view, here.