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BY 4.0 license Open Access Published by De Gruyter Open Access February 22, 2023

High-energy proton detector based on semiconductor telescope

  • GuoHong Shen EMAIL logo , ShenYi Zhang , Lin Quan , Chao Tian , HuanXin Zhang , Zheng Chang , XianGuo Zhang , Xin Zhang , Ying Sun , Ze Yang and Yueqiang Sun
From the journal Open Astronomy


Space radiation particles will cause a variety of radiation effects on orbiting satellites, such as single event effects, total ionizing dose, displacement damage, etc. In response to these space radiation effects, BeiDou Navigation satellites M15/M16 operating in medium earth orbit (MEO) developed the first integrated monitor for high-energy proton and particle radiation effects, based on space particle radiation detection technology. This payload realizes the joint observation of the high-energy proton environment, particle radiation linear energy transfer spectrum, and total radiation dose in the MEO. According to the detection data, research on the characteristics and laws of the space particle radiation effects can be carried out, and the problem of spacecraft reliability verification in orbit can be solved from the causal chain. In this article, we have introduced the high-energy proton detector (energy range 3–300 MeV), including technical indicators, working principles, instrument design, and ground calibration.

1 Introduction

The BeiDou Navigation Satellite System is a satellite navigation system constructed and operated by China itself. The navigation satellite orbit medium earth orbit (MEO) is located in the central area of the outer radiation zone, at the far end of the Earth’s magnetic field protection. It is greatly affected by the disturbance of the solar-terrestrial space environment. The space environment of the orbit is complex and harsh. Lots of charged particles in orbit can cause various radiation effects, including single event effects, displacement damage effects, total dose effects, deep charge and discharge effects, and surface charge and discharge effects (Yang et al. 2008, Pu and Ye 1993). These radiation effects threaten the safety of spacecraft (Wang et al. 1999, Xue et al. 2012). To effectively reduce or mitigate the damage of satellites from radiation effects, it is necessary to improve the ability to quantitatively describe and predict the radiation environment of typical satellite orbits. This ability also helps to reduce the waste of over-design and management costs in the development and control processes. Achieving this goal will undoubtedly require a large amount of measured space environment detection data and various empirical models based on the measured data.

Based on the current research status of particle radiation detection in the MEO orbit for navigation, M15/M16 satellites are equipped with space environment detectors, such as the high-energy proton detector (HEPD), the linear energy transfer (LET) spectrum detector, and the radiation dosimeter. This project first carried out the joint detection of the space high-energy proton energy spectrum, the LET spectrum, the total radiation dose, and a single event upset. It can monitor the changes of orbital space environment in real time and accumulate detection data. At the same time, to carry out the design of orbiting satellites and guarantee on-orbit management, we have designed and developed high-energy proton and single-event risk monitors.

2 Instrument description

2.1 Main technical indicators

Navigation satellite M15/M16 operates in the MEO orbit at an altitude of 22,000 km. In this orbit, the satellite will encounter environments such as weightlessness, vacuum, high and low temperatures, electromagnetic radiation, charged particles, micrometeors, and debris. The impact of charged particles on satellites is the most serious (Feng et al. 2007, Ye and Dou 1997).

The space radiation environment is modulated by solar activity with 11-year periodic changes, which is similar to the ground climate with long-term changes (Selesnick et al. 2016, 2010, Gussenhoven et al. 1994, Baker et al. 2016, Burch et al. 2005, Lyons and Thorne 1972, Hess 1968). In the peak year of solar activity, the MEO contains not only high-energy electrons but also a large number of high-energy protons emitted from the solar proton event (SEP) (Lazutin et al. 2007, Miroshnichenko et al. 2001, Schulz and Lanzerotti 1974). Because the geomagnetic field of the MEO orbit is weaker than that of the low Earth orbit (LEO), it cannot form the same shielding of high-energy protons as the LEO. Therefore, the flux and duration of high-energy protons will be much greater than in LEO during the SEP, causing vital damage to satellites.

The HEPD monitors the high-energy proton events generated during solar activity. It can obtain data on the evolution of the energy spectrum of high-energy protons in orbital space over time and space. The detection result provides support for the location of abnormal satellite faults and on-orbit risk assessment.

The primary technical indicators of HEPD are shown in Table 1.

Table 1

Main technical indicators of HEPDs for M15/M16

Detector Energy range Time resolution Field of view Geometric factor Sensor structure
HEPD 3–300 MeV, divided into seven channels (3 MeV ∼ 5 MeV ∼ 15 MeV ∼ 25 MeV ∼ 40 MeV ∼ 80 MeV ∼ 150 MeV ∼ 300 MeV) 1 s 40° 0.30 cm2 sr D1: Ion injection (500 μm)
D2–D5: (1 mm)

2.2 Operating principles

The HEPD sensor system uses silicon semiconductor detectors. When high-energy particles enter the sensor through the collimator, their energy is deposited in each semiconductor detector and generates respective electron–hole pairs through ionization. Under the high-voltage electric field, these electron–hole pairs converge at the output terminal and generate charge pulses. The charge pulse height is proportional to the particle energy deposited by the particles in the semiconductor detector. According to the pulse height, we can obtain information on the particle spectrum by signal discrimination threshold analysis and coincidence or anti-coincidence processing (Ye 1986, Jiao 2002).

The sensor system uses five ion-injected silicon semiconductor sensors with different thicknesses. The sensor system measures the energy loss of particles in the sensors, converts the energy into electrical signals, and provides these electrical signals to subsequent electronic circuits for analysis. According to the signal from the sensors, combined with the amplitude analysis and appropriate logical working methods, the energy spectrum and flux of high-energy protons can be measured.

The physical simulation of this detection scheme is fulfilled by Geant4 software. Figure 1 shows the energy loss curve of high-energy protons in different sensors obtained by Monte Carlo simulation. According to the simulation results, we can determine the number of energy channels and the logical working manner of the detector.

Figure 1 
                  Simulation curve of high-energy proton energy loss.
Figure 1

Simulation curve of high-energy proton energy loss.

2.3 Instrument design

The HEPD includes three parts: a collimator, sensors, and an electronics system. Figure 2 shows the probe structure schematic diagram of the HEPD.

Figure 2 
                  Schematic diagram of the HEPD structure.
Figure 2

Schematic diagram of the HEPD structure.

2.3.1 Collimator design

The collimator system has two functions. One is to form a suitable field of view and to determine the instrument’s geometric factor (Zhang et al. 2014). The other is to provide a shielding condition to prevent the obliquely incident particles from interfering with the sensor. The collimator system mainly includes three parts: the outer structure, the anti-scattering structure, and the light-blocking layer, as shown in Figure 2. The outer structure and the anti-scattering structure determine the instrument's geometric factor. The deflection magnet deflects the electrons incident on the collimator, and the light-blocking layer shields the interference of sunlight.

The outer structure is the support and shielding structure of the outermost layer of the probe. The outer structure is a cup-shaped structure with a small lower part and a large upper part. An additional copper shield is added to the outside of the probe to reduce the impact of oblique incident particles on measurement.

At the same time, to reduce the elastic scattering effect of electrons in the material, an anti-scattering structure is added inside the collimator to prevent particle scattering from interfering with the measurement (Figure 3).

Figure 3 
                     Anti-scattering structure.
Figure 3

Anti-scattering structure.

The purpose of the light-blocking layer is to block sunlight and micrometeoroids. There are three primary considerations in the design of the light-blocking layer, as follows:

  • First, the light-blocking layer must effectively block sunlight. Because the silicon sensors are sensitive to visible light, they must be shielded from the interference of visible light.

  • Second, the thermal characteristics and mechanics of the light-blocking layer must be good enough to ensure that it is not damaged during temperature changes and mechanical vibrations.

  • Third, the light-blocking layer should not be too thick, since a light-blocking layer will reduce the energy of incident particles, and a too-thick light-blocking layer will increase the lower limit of the measurement.

In this detector, a 15 μm aluminum film that can block protons below 1 MeV and electrons below 30 keV is adopted.

Permanent magnets in the collimator deflect electrons and aim to eliminate the interference of high-energy electrons and the influence of radiation. For high-energy protons and electrons of the same energy, the energy loss in the silicon semiconductor sensors is the same. The circuit is impossible to identify them. Therefore, a deflection magnet is used inside the instrument to deflect the high-energy electrons and prevent them from entering the silicon sensors.

The basic shape of the deflection magnet in this scheme is a permanent magnet magic ring structure (Zhang and Wang 2007). The central magnetic field strength can reach 4,200 Gs, which can effectively remove the electrons at <1 MeV. In addition, pure iron with high magnetic permeability can shield the magnetic field of the permanent magnet and reduce the magnetic distance of the instrument. Figure 4 shows the simulation results of the magnetic field strength.

Figure 4 
                     Simulation of the magnetic field strength of the magnet.
Figure 4

Simulation of the magnetic field strength of the magnet.

2.3.2 Sensor system design

Semiconductor sensors can receive charged particles incident on the probe. Ion-injected silicon semiconductor sensors are currently the best-performing semiconductor sensors in terms of linear response range, energy resolution, and spatial applicability.

In this scheme, the sensor system adopts the traditional semiconductor detector telescopes. It uses five ion-injected silicon sensors and forms a 40° detection field of view when combined with the collimator. Through the installation location on the satellite, it is in the shadow of the sun during flight. The direction when monitoring on orbit is perpendicular to the magnetic field line, and it is the maximum particle flux direction. The function of the sensor system is to measure the energy loss of charged particles in the semiconductor detector, convert the energy into electrical signals, and provide them to subsequent electronic circuits for analysis. Amplitude analysis and a proper logical working method for processing the sensor signals can obtain the energy spectrum and flux of the particles. Ion-injected semiconductor sensors that have good energy resolution are the mainstream sensors currently in use.

According to the indicator design of the instrument, the specific indicators of the sensors are as follows. The first sensor’s thickness is 300 μm, remaining four sensors’ thickness is 1 mm. The detector geometric factor, which represents the ability of the detector to accept particles, is affected by the diameter of the sensors. The diameter of the sensors in the proton detector is 12 mm. The design of the detector can detect the responses of different energy protons in the sensors and derive the energy of the incident proton according to the simulation results.

2.3.3 Electronics design

The electronic design of the HEPD mainly includes the front-end analog electronic circuit, the back-end digital acquisition and processing circuit, and the satellite bus interface. The front-end signal processing circuit performs pre-amplification, pulse shaping, master amplification, and peak hold processing on the charge pulse output by the semiconductor sensors. Then the signal is sent to the back-end digital circuit part, and the analog-to-digital conversion (ADC) completes the analog-to-digital conversion of the peak protection signal. The field programmable gate array (FPGA) circuit mainly accomplishes data processing, compression, storage, and packaging of the signals collected by the ADC. The FPGA also communicates with the satellite through the interface bus and downloads the detection data packets. In addition, the instrument electronics also includes power modules, noise detection circuits, telemetry interfaces, temperature detection circuits, and sensor bias circuits. The electronics principle of the HEPD is shown in Figure 5.

Figure 5 
                     Block diagram of the instrument electronics.
Figure 5

Block diagram of the instrument electronics.

2.3.4 Installation design

The HEPD was installed inside the satellite, facing the sky. Its collimator extends out of the satellite skin, and there is no shielding in the detection field of view. The cone-shaped detection field of view axis points to the satellite’s nightside. The parameter relationship of the HEPD is shown in Figure 6.

Figure 6 
                     Schematic diagram of the instrument’s parameter relationship.
Figure 6

Schematic diagram of the instrument’s parameter relationship.

3 Calibration and performance

The purpose of ground calibration for the HEPD is to verify and accurately provide detection indicators, including proton energy channels division and flux accuracy.

3.1 Energy calibration

Energy calibration evaluates each energy channel’s measurement error. The evaluation result determines the actual energy index and detection accuracy of the instrument. The energy range calibration determines the actual demarcation point of the detector’s energy channel range. The basic principle is that when a particle with the energy of the demarcation point enters the detector, the probability of it falling into the upper and lower energy levels is equal. It can be expressed by the following equation:

(1) P ( i , E i ) = P ( i + 1 , E i ) ,

where i is a certain energy range, E i is the actual energy demarcation, and P is the probability of particles falling into the energy range.

During calibration, the entire HEPD measures the single-energy proton beam that is continuously adjustable and output by the accelerator. The response of the detector to protons with different energies can be obtained. According to the actual situation of the response, the actual energy range of each channel can be obtained. Adjusting the particle beam energy and combining with measured data fitting can find the beam energy when the counts of two adjacent channels are equal, that is, the actual measurement boundary of the energy boundary.

As shown in Figure 7, when looking for the actual boundary point between the two energy ranges of P n–1 and P n , the proton beam energy selects multiple energy points. The two lines represent the probability that different energy protons fall into energy ranges P n–1 and P n , respectively. When the two lines intersect, it means that the probability of particles falling into the two channels is equal. The incident energy corresponding to the intersection of the two lines is the boundary point of the actual energy range of P n−1 and P n .

Figure 7 
                  Principle of energy range calibration.
Figure 7

Principle of energy range calibration.

For the high-energy range that the accelerator cannot cover, we use the result of the coverage energy to perform linear fitting and extension.

The calibration experiment is carried out with the accelerator device, and the experiment scheme is shown in Figure 8. The instrument is installed in the vacuum tank of the accelerator. The center of the sensor is at the same height as the particle beam, and the incident beam is within the field of view of the detector. The output of the HEPD is transmitted to the data acquisition device after passing through the ground test box.

Figure 8 
                  Block diagram of the energy calibration experiment.
Figure 8

Block diagram of the energy calibration experiment.

In the calibration experiment, plural proton beams with specific energy irradiate the detector. The response of different energy beams is analyzed to determine the deviation between the actual measured value and the designed value of each energy channel of the instrument. We conducted the calibration experiment at the National Key Laboratory of Heavy Ion Accelerator, Institute of Modern Physics, Chinese Academy of Sciences. During the experiment, we calibrated the detector’s threshold energy with 15, 25, 40, and 80 MeV by adjusting the proton beams’ energy. The calibration result of the proton energy spectrum is shown in Figure 9. Through analysis, the error of energy channel division is less than 5%, which meets the requirements.

Figure 9 
                  Energy calibration results of the proton energy spectrum at 15, 25, 40, and 80 MeV. Energy of (a) 15 MeV boundary fitting, (b) 25 MeV boundary fitting, (c) 40 MeV boundary fitting, and (d) 80 MeV boundary fitting.
Figure 9

Energy calibration results of the proton energy spectrum at 15, 25, 40, and 80 MeV. Energy of (a) 15 MeV boundary fitting, (b) 25 MeV boundary fitting, (c) 40 MeV boundary fitting, and (d) 80 MeV boundary fitting.

Due to the limitations of accelerator beam conditions, this calibration cannot cover the entire energy range. The calibration of the uncovered energy limitation is based on the relationship between the actual value obtained in the calibration test and the designed value, which is obtained by linear fitting and extension.

3.2 Flux accuracy calibration

The purposes of proton flux calibration are as follows: calibrate the actual counting capacity of the load, test the effective counting capacity range and the accuracy of the flux test, obtain the corresponding accuracy of the detector’s flux (i.e., the relationship between the output and the incident particle count), determine the detection sensitivity, and finally evaluate the influence of the background noise count on the detector.

Theoretically, the flux error can be directly calibrated by the particle source with a known flux. But in fact, the particle flux is not stable regardless of the accelerator or the radioactive source. So there is no accurate and reliable method to directly calibrate the flux. Therefore, to calibrate the particle flux error, the indirect method is usually used to decompose the flux error into various errors that contribute to it, measure them separately, and then add them to obtain the total flux error.

The direct detection quantity of the detector is the particle count N (s−1). The data must be normalized to facilitate data comparison. We can obtain the flux of the instrument through the count (N) divided by the geometric factor (G), as follows:

(2) M ( cm 2 s 1 sr 1 ) = N ( s 1 ) G ( c m 2 sr ) .

Therefore, the instrument count accuracy and geometric factor accuracy affect the flux calibration accuracy (Figure 10). The count, which is directly related to the detector’s sensors and electronics, is the most primitive output data of the detector. Therefore, the count error includes the response error of the sensors and electronics.

Figure 10 
                  Factors affecting flux accuracy calibration.
Figure 10

Factors affecting flux accuracy calibration.

Assume that the relative detector flux M is σ M , the relative count accuracy is σ N , and the relative geometric factor is σ G . According to the error transfer formula σ y 2 = i y x 2 σ xi 2 , the relative accuracy of flux is σ M 2 = σ N 2 + σ G 2 .

The sensor count error calibration uses the same batch of silicon semiconductor detectors to test them separately. Place the sensor in the test box and use a Bi207 radiation source to irradiate the sensor. The total count per unit of time is recorded by the dedicated multi-channel system for sensor measurement. Repeat the above steps continuously to obtain a series of count rates (n i ). Finally, the counting response error of the batch of sensors is obtained by calculating the standard deviation as follows:

(3) 1 n 1 i = 1 n ( n i n ¯ ) 2 .

The electronic count error calibration is mainly done through a software program using the random function generator to simulate the time distribution of the space particle incident on the sensors. Assume the signal collection time of the instrument is t, and if the time difference between the incidents of the two particles is less than t, only record the bigger signals. Record the actual count and the “eaten” count due to signal superposition to obtain the electronic count error of the detector. The particle incidence with different fluxes can be used in the calibration to obtain the corresponding relationship between the number of incident particles and the output count of the detector.

The geometric factor is a vital characteristic parameter of the detector. It is a necessary parameter for data normalization and data comparison. The geometric factor is related to the instrument’s geometric structure and the interference of particles with different energies and different types on each energy channel count. The geometric factor needs to be simulated and calculated by combining the geometric structure and the physical processes of various particles. Using the same input parameters to simulate the geometric factor value G i of each energy channel. Then calculate the geometric factor error σ G according to the error transfer function.

According to the calculations of electronic count error, sensor count error, and geometric factor error, we can obtain the actual flux error as shown in Table 2.

Table 2

The flux error of the HEPD

Electronic count error Sensor count error Geometric factor error Flux error
Error 0.95% 4.8% 3% 8.75%

4 Conclusions

The HEPD proposed in this article has carried out high-energy proton energy spectrum and flux detection on the navigation MEO orbit. The detector’s performance indicators have been verified by ground calibration experiments. The satellite was launched in December 2019. The HEPD has acquired a large amount of on-orbit space environment detection data, which has been applied to the on-orbit management and anomaly analysis of spacecraft. Furthermore, it will effectively promote Chinese development of basic research on the application of space environment and its effects.


This work is supported by the Aerospace Engineering Institute. The authors thank the management and operators of the China Institute of Atomic Energy and the Institute of Modern Physics in Lanzhou for their efforts to make excellent beam time available.

  1. Funding information: The authors state no funding involved.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Conflict of interest: Authors state no conflict of interest.


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Received: 2022-07-14
Revised: 2022-09-08
Accepted: 2022-09-09
Published Online: 2023-02-22

© 2023 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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