Power Consumption

CubeStar's instantaneous power consumption depends on the task it is currently exe- cuting. To determine the instantaneous current consumption, CubeStar's power supply was monitored with an INA139 current shunt monitor, while it performed a typical star matching iteration. The results show that CubeStar goes through four distinct power consumption modes, as shown in Figure 6.6.

CubeStar begins in idle mode (Mode 1), where the processor is waiting for a new com- mand and the imager is in low power/disabled mode. Next, the imager is switched on while the rst, invalid image is clocked out (Mode 2). The largest power consumption

Figure 6.6: CubeStar's measured current consumption during a typical iteration of 1000 ms

Mode Current Consumption (mA) Time Period (ms)

1 71.2 140

2 121.2 68

3 177.3 388

4 81.81 404

Table 6.2: CubeStar's current consumption in dierent modes

occurs next, while the image sensor is taking a new image and the processor is process- ing the previous image (Mode 3). The fourth power consumption mode occurs while the image data is being transferred from the FPGA's SRAM to the processor's SRAM (Mode 4). The image sensor is disabled during the image transfer. Once the image transfer is complete, CubeStar goes back into idle mode.

Table 6.2 lists the current consumed during each mode, and the time spent in each mode during a typical 1000 ms iteration.

CubeStar operates o a single 3.3 V supply, so it is simple to determine its power consumption from its current consumption. From Table 6.2 it is evident that the max- imum power consumption required by CubeStar is 0.585 W during mode 2. CubeStar's average power consumption over one iteration is given by Equation 6.3.1.

Poweravg = 4 X n=1 PnTn = 396.2mW (6.3.1) where

Pavg =The average power in mW over a 1000ms iteration Pn=The power consumed during mode n

Tn=The time spent in mode n in seconds

Without the two onboard LED's, which would be removed for ight models, the average power consumption would be closer to 350mW.

More power could be saved by turning the camera o completely during the idle and image transfer modes, instead of disabling it. However, the current CubeStar hardware does not allow this option.

Chapter 7

Conclusion and Recommendations

This chapter presents a brief summary of the results of each section, draws conclusions with regards to the original goals of the project and makes recommendations for the future of CubeStar.

7.1 Summary and Conclusions

Chapter 1 gave a brief introduction to CubeSats, CubeSat ADCS performance and star trackers. It discussed the advantages of adding a star tracker to current CubeSat attitude determination and control systems and outlined the basic goals of the CubeStar project. The relevance of this research topic with respect to the CubeSat community was emphasized by the description of four other nano star tracker projects, most of which are still ongoing.

Chapter 3 described the design process of CubeStar. Existing subsystems would be reused from CubeSense and CubeComputer in order to develop a star tracker within two years. A suitable image sensor with enough sensitivity was found in the automotive industry. The image sensor costs under R500, requires relatively low power and has an interface similar to the CubeSense cameras. A high quality, commercial lens with a suitable FOV was found for under R400. Together, the image sensor and lens allow cubeStar to detect stars with magnitudes down to 3.8 over a 51 x2 7 degree FOV. This was proven to be sucient for keeping at least three stars within the FOV over 99.9% of the celestail sphere.

Chapter 4 described the algorithms involved in matching stars and estimating attitude. The image plane search, region growing and centroiding algorithms were reused from SUNSAT's star tracker for detecting and extracting stars from the raw star images. It

was proven that these algorithms were ecient and could achieve sub-pixel accuracy by testing them on simulated and real sky images. CubeStar's star matching algo- rithm, called the Geometric Voting Algorithm, was described in detail. The matching algorithm was proven to provide a lost-in-space match over 93% of the celestial sphere and an assisted match over 98.5% of the celestail sphere. A tracking algorithm with coverage over 100% of the celestial sphere was also described.

The QUEST algorithm was chosen as CubeStar's attitude estimation algorithm due to its long space heritage. The complete set of algorithms was tested by inputting a simulated sky image, generated with a known attitude, and comparing this known attitude to the output of the QUEST algorithm. The algorithms were proven to provide an accuracy of better than 0.01 degrees in the absence of image noise or lens distortion. Chapter 5 described the implementation of CubeStar. The hardware was implemented as three separate 3 x 4.5 cm circuit boards stacked behind one another to make optimal use of the limited space onboard CubeSats. An engineering model was completed and simple calibration procedures were developed. CubeStar weighs less than 90 g without a bae or case and takes up less than 0.25 U volume, making it one of the smallest star trackers in existence. CubeStar achieves a 1 Hz update rate by performing the image capture and processing in parallel. However, the current hardware design wastes a signicant amount of time transfering images between the FPGA and processor. This has a negative impact on the age of the outputted attitude data which may cause problems for accurate ADCS performance. A solution to the problem, involving the use of a single shared SRAM, was proposed for implementation on the next iteration of CubeStar.

Chapter 6 described the tests performed on the engineering model of CubeStar. CubeStar was taken outside for real night sky tests to determine its accuracy and tracking per- formance. The tests veried the operation of CubeStar in all modes and proved that CubeStar could achieve a 1σ accuracy of 0.0072 degrees across the boresight and 0.0203 degrees around the boresight. A slew test conrmed that CubeStar will operate cor- rectly on a nadir pointing satellite and can handle slew rates up to 0.1333 deg/s. Slew rates up to 0.3 deg/s should be possible with the current rmware.

Table 7.1 lists the specications of CubeStar V1. These specication can be compared with the original goals of the project. CubeStar's volume is under 0.5U, its average power consumption is under 0.5W and it achieves the desired accuracy of 0.01 degrees. Table 7.2 gives an approximate component cost breakdown. Considering commercial star trackers cost upwards of R100 000, a component cost of R1970 qualies CubeStar

Specication Value Units

Weight <90 g

Dimensions 46 x 33 x 70 mm

Accuracy (cross bore) better than 0.01 deg RMS

Accuracy (roll) better than 0.03 deg RMS

Power (avg/peak) 350/550 mW

Operating Voltage 3.3 V

Data Interface I2C/UART -

Table 7.1: CubeStar V1 Specications (without enclosure or bae)

Component Cost (ZAR)

Image Sensor 410 Lens 380 Gecko Processor 100 FPGA 180 PCBs 400 Other 500 TOTAL 1970

Table 7.2: Approximate component cost breakdown

as a low cost star tracker. Therefore, all specications have been met or exceeded. Most importantly, however, the CubeStar project has successfully delivered a working nano star tracker in under two years. A second generation CubeStar is scheduled to y onboard ZA-AeroSat in 2015 as part of Stellenbosch University's contribution to the QB50 Project.