An adaptive strategy for optimal photon number in quantum interferometry radar under stratocumulus cloud background

Abstract

The disclosed embodiment is about an adaptive strategy for the optimal photon number of a quantum interferometer radar under a stratocumulus cloud background. It includes: a QIR system generates detection photons and reference photons with preset photon numbers, and directs the detection photons toward the detection target; the QIR system receives the reflected detection photons; a mathematical model is established based on the influence of the scattering, absorption, and other characteristics of the liquid water content of the stratocumulus clouds in the atmospheric environment on the reflected detection photons, and the relationship between the liquid water content of the stratocumulus clouds, the number of radar transmitter signal photons, and the transmission distance of the detection photons is obtained; based on the relationship between the liquid water content of the stratocumulus clouds, the number of transmitter signal photons, and the transmission distance of the detection photons, the number of radar transmitter photons is adaptively adjusted so that the radar system can achieve the optimal average photon number. The disclosed embodiment effectively improves the robustness of the QIR system under the water content of stratocumulus cloud particles by adjusting the average photon number of the QIR system in real time.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the field of communication technology, and in particular to an optimal photon number adaptive strategy for quantum interferometer radar under a stratocumulus cloud background. Background Art

[0002] Quantum Interference Radar (QIR) is a research hotspot and frontier in this field. Research has demonstrated that QIR can improve the sensitivity of optical interferometers by modifying the input state of light, such as compressed or entangled states, thereby breaking through the quantum limit of shot noise and approaching the Heisenberg limit. Quantum interferometer radar uses quantum entangled signals to detect targets. However, quantum signals are prone to entanglement with various particles in the surrounding atmosphere, resulting in quantum decoherence, which can affect resolution and channel survival function.

[0003] In related technologies, the liquid water content of stratocumulus cloud particles can negatively impact the resolution and system survival function of QIR. Increasing the emitted photon energy can improve both resolution and the system survival function, thereby enhancing system reliability. Research into the impact of the number or energy of emitted photons and stratocumulus clouds on QIR performance has not yet been conducted.

[0004] Therefore, it is necessary to improve one or more problems existing in the above-mentioned related technical solutions.

[0005] It should be noted that this section is intended to provide background or context for the technical solutions of the present disclosure stated in the claims. The description herein is not admitted to be prior art by virtue of being included in this section. Summary of the Invention

[0006] The purpose of the embodiments of the present disclosure is to provide an optimal photon number adaptation strategy for quantum interferometer radar under a stratocumulus cloud background, thereby overcoming one or more problems caused by the limitations and defects of related technologies to at least a certain extent.

[0007] According to an embodiment of the present disclosure, a strategy for adapting the optimal photon number of a quantum interferometer radar under a stratocumulus cloud background is provided, including:

[0008] The QIR system generates detection photons and reference photons, each of which has a preset number of photons, and emits the detection photons toward a detection target;

[0009] The QIR system receives the reflected detection photons, wherein after the detection photons pass through the stratocumulus cloud, the detection target reflects them back to the QIR system;

[0010] Based on the influence of the scattering and absorption characteristics of the liquid water content of stratocumulus clouds in the atmosphere on the reflected detection photons, a mathematical model was established to obtain the relationship between the liquid water content of stratocumulus clouds, the number of signal photons at the radar transmitter, and the transmission distance of the detection photons.

[0011] Based on the relationship between the liquid water content of stratocumulus clouds, the number of signal photons at the transmitting end, and the transmission distance of the detection photons, the number of photons at the radar transmitting end is adaptively adjusted so that the radar system can achieve the optimal average photon number.

[0012] The average photon number is adaptively adjusted using the optimal average photon number.

[0013] In one embodiment of the present disclosure, the QIR system includes:

[0014] Entangled state light source and detection signal processing system.

[0015] In one embodiment of the present disclosure, the steps of generating detection photons and reference photons with a predetermined number of photons in the QIR system and directing the detection photons toward a detection target include:

[0016] The entangled state light source generates the preset number of entangled photon pairs, and the entangled photon pairs are split into the detection photons and the reference photons by a beam splitter;

[0017] The transmitting end of the QIR system emits the detection photons toward the detection target, and the control photons remain in the QIR system as local photons.

[0018] In one embodiment of the present disclosure, the step of establishing a mathematical model based on the reflected detection photons and the reference photons includes:

[0019] respectively obtaining the parameters of the reflected detection photons, the parameters of the control photons, and the parameters of the QIR system;

[0020] The mathematical model is obtained according to the parameters of the reflected detection photons, the parameters of the control photons and the parameters of the QIR system.

[0021] In one embodiment of the present disclosure, the parameters of the reflected detection photons, the parameters of the reference photons, and the parameters of the QIR system include at least:

[0022] The number of photon pulses of the detection photons generated by the QIR system, the probability that the reflected detection photons are detected by the QIR system, the total dark registration rate of the receiving end detector of the QIR system, the probability that the receiving end detector of the QIR system responds, the internal loss of the receiving end detector of the QIR system and the density of the average photon number.

[0023] In one embodiment of the present disclosure, the step of obtaining the mathematical model includes:

[0024] Establishing an equation for a pulse photon passing rate based on the number of photon pulses of the detection photons generated by the QIR system, the total dark record rate of the receiving end detector of the QIR system, the probability of the receiving end detector of the QIR system responding, and the density of the average photon number;

[0025] Obtaining a total transmission rate of the channel under the stratocumulus background based on the internal loss of the receiving detector of the QIR system, the extinction coefficient of the stratocumulus cloud particles, and the transmission distance of the detection photons;

[0026] Obtaining a pass rate of the photon pulses of the detection photons according to a total transmission rate of the channel under the stratocumulus cloud background and the number of photon pulses of the detection photons generated by the QIR system;

[0027] Obtaining the probability of a receiving-end detector of the QIR system responding by using the pass rate of the photon pulse of the detection photon and the probability that the reflected detection photon is detected by the QIR system;

[0028] The mathematical model is obtained based on the equation of the pulse photon pass rate, the total transmission rate of the channel under the stratocumulus cloud background, the pass rate of the photon pulse of the detection photon and the probability of the response of the receiving end detector of the QIR system.

[0029] In one embodiment of the present disclosure, the formula of the mathematical model is:

[0030]

[0031] Among them, Q μ is the pulse photon passing rate, μ is the average photon number density, Y0 is the total dark record rate of the receiving detector, η cloud is the total transmission rate of the channel under the stratocumulus background, η det is the internal loss of the detector at the receiving end, k cloud is the extinction coefficient of stratocumulus cloud particles.

[0032] In one embodiment of the present disclosure, the formula for the optimal average number of photons is:

[0033]

[0034] Among them, μ aver is the optimal average number of photons, C LW is the liquid water content of stratocumulus cloud particles, ρ is the density of water, r eff is the effective radius of stratocumulus cloud particles, e dis the detection bit error rate of the detector at the receiving end.

[0035] In one embodiment of the present disclosure, the step of adaptively adjusting the average photon number using the optimal average photon number includes:

[0036] If the water content of the stratocumulus cloud particles increases, the average number of photons is increased;

[0037] If the water content of the stratocumulus cloud particles decreases, then the average number of photons is reduced;

[0038] If the water content of the stratocumulus cloud particles remains unchanged, the average number of photons remains unchanged.

[0039] The technical solutions provided by the embodiments of the present disclosure may have the following beneficial effects:

[0040] In the embodiments of the present disclosure, the optimal photon number adaptive strategy of quantum interferometer radar under the above-mentioned stratocumulus cloud background is used to establish the relationship between the liquid water content of stratocumulus clouds, the average photon number of detection photons, and the transmission distance of detection photons, and the optimal average photon number is obtained. Finally, the average photon number is adaptively adjusted using the optimal average photon number. By adjusting the average photon number of the QIR system in real time, the robustness of the QIR system under the water content of stratocumulus cloud particles is effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification, are used to explain the principles of the present disclosure. Obviously, the drawings described below are only some embodiments of the present disclosure, and those skilled in the art can derive other drawings based on these drawings without inventive effort.

[0042] Figure 1 A diagram showing the steps of an optimal photon number adaptation strategy for a quantum interferometer radar under a stratocumulus cloud background in an exemplary embodiment of the present disclosure;

[0043] Figure 2 A schematic diagram illustrating a QIR system in an exemplary embodiment of the present disclosure is shown;

[0044] Figure 3 A graph showing the relationship between the communication link attenuation factor, the transmission distance, and the liquid water content of stratocumulus clouds in an exemplary embodiment of the present disclosure is shown;

[0045] Figure 4 A flow chart showing an adaptive strategy for the number of trapped state photons in an exemplary embodiment of the present disclosure is provided;

[0046] Figure 5A graph showing the relationship between the average number of photons, the liquid water content of stratocumulus clouds, and the transmission distance under the PNA algorithm strategy in an exemplary embodiment of the present disclosure is shown;

[0047] Figure 6 A diagram showing a transmission model of a QIR system optical signal in stratocumulus clouds in an exemplary embodiment of the present disclosure is shown;

[0048] Figure 7 A graph showing the relationship between QIR angular resolution, stratocumulus liquid water content, and stratocumulus particle concentration under an algorithm strategy without using PNA in an exemplary embodiment of the present disclosure is shown;

[0049] Figure 8 A graph showing the relationship between QIR angular resolution, stratocumulus liquid water content, and stratocumulus particle concentration under the PNA algorithm strategy in an exemplary embodiment of the present disclosure is shown;

[0050] Figure 9 The relationship between the channel survival function of the QIR system and the liquid water content of stratocumulus clouds before and after the PNA algorithm is adopted in the exemplary embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0051] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0052] In addition, the accompanying drawings are merely schematic illustrations of embodiments of the present disclosure and are not necessarily drawn to scale. Like reference numerals in the figures represent like or similar parts, and thus repeated descriptions thereof will be omitted. Some of the blocks shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically separate entities.

[0053] This example embodiment first provides an optimal photon number adaptation strategy for quantum interferometer radar under stratocumulus cloud background. Figure 1 As shown in , the method may include: Steps S101 to S105

[0054] Step S101: The QIR system generates detection photons and reference photons, both of which have a preset number of photons, and emits the detection photons toward a detection target;

[0055] Step S102: The QIR system receives the reflected detection photons, wherein the detection photons are reflected back to the QIR system by the detection target after passing through stratocumulus clouds;

[0056] Step S103: establishing a mathematical model based on the reflected detection photons and the reference photons, and obtaining a relationship between the liquid water content of the stratocumulus cloud, the average number of detection photons, and the transmission distance of the detection photons;

[0057] Step S104: obtaining an optimal average number of photons according to the relationship between the liquid water content of the stratocumulus cloud, the average number of detection photons, and the transmission distance of the detection photons;

[0058] Step S105: Adaptively adjust the average photon number using the optimal average photon number.

[0059] Through the above-mentioned quantum interferometer radar optimal photon number adaptive strategy under the stratocumulus cloud background, the relationship between the liquid water content of stratocumulus clouds, the average photon number of detection photons and the transmission distance of detection photons was established, and the optimal average photon number was obtained. Finally, the optimal average photon number was used to adaptively adjust the average photon number. By adjusting the average photon number of the QIR system in real time, the robustness of the QIR system under the water content of stratocumulus cloud particles was effectively improved.

[0060] Below, we will refer to Figures 1 to 9 The various parts of the optimal photon number adaptation strategy for the quantum interferometer radar under the stratocumulus cloud background in this example embodiment are described in more detail.

[0061] In step S101, QIR belongs to entangled photon radar, and its system is as follows Figure 2 As shown in Figure 1, QIR mainly includes an entangled light source and a detection signal processing system. The entangled light source generates an entangled photon pair, which is then split into a reference photon and a detection photon by a beam splitter. The detection photon is emitted to the target through the transmitter, while the reference photon remains as a local photon in the quantum radar system.

[0062] In step S102, after the detection photon is emitted from the transmitting end, it detects the target area and is then reflected back to the local radar system by the target. Due to the different paths, there is an optical path difference between the detection photon and the control photon, which in turn produces a certain phase difference. Therefore, the two entangled photons are re-interfered when returning, and the attenuated quantum interferometry method is used to measure the phase difference to obtain the distance information of the detected target.

[0063] In addition, stratocumulus clouds are actually a type of water cloud. In actual research, stratocumulus cloud particles are often unevenly distributed, and the main distribution inside is liquid water. Therefore, this application uses a modified gamma function and combines it with Mie scattering theory for fitting. The particle size distribution function n(r) is selected to describe the average size distribution of stratocumulus cloud particles as follows:

[0064] n(r)=arα exp(-br γ ) (3)

[0065] Where r represents the radius of the stratocumulus cloud particle, a, b, α, and β are all positive constants, and for stratocumulus clouds, γ = 1.

[0066] Liquid water content C of stratocumulus cloud particle distribution LW It can be expressed as:

[0067]

[0068] Where C LW It is usually between 0.01 and 1, and the unit is g / cm 3 ; Density of water ρ = 1g / cm 3 .

[0069] Among the properties of stratocumulus clouds, it is known from the known literature that its effective radius is mainly in the range of 5μm≤r eff ≤15μm. According to Mie scattering theory, the extinction coefficient k of stratocumulus cloud particles can be cloud Expressed as:

[0070]

[0071] Where: Since the radius of stratocumulus cloud particles r>>λ, the extinction efficiency factor Q ext ≈2. Its average extinction coefficient is:

[0072]

[0073] Combining equations (3)(4)(5)(6) yields the relationship between the water content of stratocumulus clouds and the extinction coefficient:

[0074]

[0075] According to the Bouguer-Lambert theorem, the communication link attenuation factor A caused by stratocumulus clouds is cloud It can be described as:

[0076]

[0077] Where: L represents the photon transmission distance, in km; the effective radius of stratocumulus cloud particles r eff = 10 μm. The simulation established the relationship between the communication link attenuation factor, transmission distance and stratocumulus liquid water content. Figure 3 shown.

[0078] Depend on Figure 3The simulation results show that when the transmission distance is 0 and the stratocumulus liquid water content is 0, the link attenuation factor is 0. When the transmission distance is 15 km, the stratocumulus liquid water content is 0.2587 g / cm 3 When the transmission distance is 20 km, the link attenuation factor is 1.906 db / km; when the transmission distance is 20 km, the liquid water content of stratocumulus clouds is 1 g / cm 3 When the link attenuation factor reaches a maximum of 8.6dB / km, it can be seen that under the influence of stratocumulus clouds, the energy of photons is greatly attenuated. Therefore, it is necessary to adopt an average photon number adaptive strategy to adjust the number of photons or photon energy at the transmitting end in real time to ensure the performance of QIR.

[0079] In step S103, the decoy state protocol defines that when the transmitter emits n photon pulses, the probability of being detected by the receiver is η n , Y0 is the total dark count rate of the receiving detector. Considering the dark count, when the transmitter emits n photon state pulses, the probability Y of the receiving detector responding is n η det is the internal loss of the detector at the receiving end. μ is the average photon number density. Pulse photon passing rate Q μ for:

[0080]

[0081] Let the total transmission rate η of the channel under the stratocumulus background be cloud for:

[0082]

[0083] Then the transmission rate η of the transmitter sending a pulse containing n photons is n for:

[0084] η n =1-(1-η cloud ) n (11)

[0085] Combined η n and Y0 can be Y n Expressed as:

[0086] Y n =η n +Y0 (12)

[0087] Substituting equations (9), (10), and (11) into equation (8), we can obtain:

[0088]

[0089] From equation (1), we can see that the larger the μ value, the higher the average photon pulse transmission rate in the stratocumulus liquid water environment, and the higher the communication efficiency. Therefore, determining the optimal μ value for the transmitter signal pulse is of great significance for improving the performance of quantum communication systems using the decoy state protocol in stratocumulus clouds.

[0090] In step S104 and step S105, due to the interaction between the qubit and the environment, a qubit polarization vector may be depolarized, resulting in quantum state decoherence. Therefore, this application studies the effect of stratocumulus liquid water content on QIR performance under a depolarized channel. The flow chart of the adaptive strategy for the number of trapped state photons adopted in this application is as follows: Figure 4 shown.

[0091] This application can send real signal μ and decoy signal based on the three-state protocol v1 , vacuum state signal v2 and satisfies v1 +v2<μ. Because its real signal state uses entangled photons, one photon is left as an idle photon in the QIR receiver, and the remaining photons and signals such as the vacuum state and the decoy state are transmitted to the target area. The signal photons are received after being reflected by the target, and the receiver detects the target by extracting the quantum correlation characteristics of the signal photons and the idle photons. The amount of liquid water contained in the stratocumulus cloud particles is judged according to the attenuation degree of the photons, and the transmitter can adaptively correct the average number of photons according to the real-time changes in the liquid water content of the stratocumulus clouds. When the water content of the stratocumulus cloud particles increases, the value of the average number of photons μ is increased, and the average number of photons sent is μ aver =μ+i; When the water content of stratocumulus cloud particles decreases, the value of the average photon number μ is reduced, and the average number of photons sent is μ aver =μ-i; When the water content of stratocumulus cloud particles is stable, the value of the average photon number does not change, that is, μ aver =μ. The ground radar station detects aerial targets by using a decoy state adaptive algorithm and adjusting the μ value of the signal state photon number in real time, thereby achieving the optimal average number of photons in the transmitted signal state under different stratocumulus cloud liquid water contents.

[0092] The quantum bit error rate of a signal containing n photons is:

[0093]

[0094] Among them, e d is the detection error rate of the detector at the receiving end; Y0 is the dark count rate of the detector; η n is the transmission efficiency of n-photon signal; e0 is the detection result of the detector when the transmitter emits zero photon signal.

[0095] Combining the GLLP formula with the decoy state protocol, the secure key generation rate of the decoy state system is obtained as:

[0096] R key ≥η cloud { - Q μ f(E μ )H2(E μ ) + Q 1[ 1-H2(E1)]} (14)

[0097] where η cloud is the system efficiency, f(E μ ) is the bilateral error correction efficiency, E μ is the bit error rate of the received photon state; Q1 is the probability of a single photon reaching the receiving end; E1 is the bit error rate caused by a single photon; the binary entropy function is: H2(x)=-xlog2(x)-(1-x)log2(1-x).

[0098] The quantum bit error rate with a signal strength of μ under a stratocumulus background can be expressed as:

[0099]

[0100] Substituting (15) into (14) can deduce the security key generation rate under the stratocumulus background:

[0101] R key ≥-η cloud μf(e d )H2(e d )+η cloud μe -μ [1-H2(e d )] (16)

[0102] The optimal average photon number μ at the transmitter of the QIR system under stratocumulus background aver satisfy:

[0103]

[0104] Formula (2) is the algorithm formula for adaptively adjusting the average photon number using the decoy state protocol under the influence of stratocumulus clouds. The simulation is as follows: Figure 5 shown.

[0105] In addition, if Figure 6 Figure 2 shows the transmission model of QIR under different stratocumulus liquid water contents. S1 represents the state when the stratocumulus liquid water content increases; S2 represents the state when the stratocumulus liquid water content is stable; and S3 represents the state when the stratocumulus liquid water content decreases.

[0106] The impact of the above-mentioned PNA (Photon Number Adaptive Algorithm) algorithm on QIR resolution

[0107] Resolution is the main parameter of QIR system, which is less affected by atmospheric loss and can be overcome by increasing the average number of photons per pulse μ. The resolution of classical radar is: δR C =λ / 2.

[0108] Without considering atmospheric attenuation, this application assumes that the spatial resolution of the radar is:

[0109]

[0110] Compared to classic radar, QIR improves the resolution by about times. (17) where δR φ is the angular resolution of the pulse signal, which is related to the full width at half maximum of the pulse signal. The more photons in the pulse signal, the smaller the full width at half maximum, the smaller the narrowband width, and the higher the QIR spatial resolution. λ is the signal wavelength. In addition, the optical thickness L2 of stratocumulus clouds can be expressed as:

[0111]

[0112] Considering the atmospheric attenuation, this application uses the parity operator method to convert the QIR spatial resolution δR Q Expressed as:

[0113]

[0114] In order to facilitate the research, this application studies δR φ To further study δR Q When the signal wavelength remains unchanged, all the φ The results of this study are applicable to δR Q .

[0115] The optimal average photon number μ aver Combined with equations (18) and (19), the QIR angular resolution after adaptive adjustment can be obtained as:

[0116]

[0117] Table 1 lists some parameter values ​​of resolution as follows:

[0118]

[0119] Therefore, the QIR angular resolution δR before and after the average photon number adaptive adjustment strategy is adopted φ Simulation was performed.

[0120] Theoretically, the higher the concentration of stratus cloud particles, the higher the liquid water content, the higher the scattering and absorption of photons, which in turn leads to lower radar resolution. Figure 7 and Figure 8 It can be concluded that under the same conditions, the higher the water content curve value, the corresponding δR φ The lower the value, the lower the resolution. When the PNA algorithm is used, the number of photons increases, and the corresponding δR under the same conditions φ The lower the value, the higher the resolution. Figure 7 and Figure 8 , when the stratocumulus cloud particle concentration N0=1 . 579×10 4 cm -3 , water content C LW =0.5g / cm 3 When the PNA strategy is adopted, as the number of photons increases, the angular resolution value of the system δR φ The number of photons decreased from 1.289 to 1.028, indicating a significant improvement in quantum radar resolution. Therefore, the adaptive photon number adjustment strategy can address the impact of stratocumulus cloud conditions. As the number of photons increases or decreases, the resolution changes accordingly.

[0121] The impact of the above PNA algorithm on the survival function of the QIR system

[0122] The survival function can be used to measure the reliability of the QIR system in free space. cloud Expressed as:

[0123] S cloud =ξ cloud ·F cloud (twenty one)

[0124] where ξ cloud is the survival coefficient of the stratocumulus channel, and 0<ξ cloud <1, its specific value depends on the water content of stratocumulus clouds. The survival coefficient in the context of stratocumulus clouds can be expressed as:

[0125] ξ cloud =5809 / 5810-9A cloud / 2905 (22)

[0126] From the above formula, we can see that the quantum radar signal is subject to link attenuation A. cloud The smaller the survival coefficient ξ cloud The bigger the F cloud It is defined as the quantum radar signal state transmission fidelity, which is used to define the similarity between the quantum input state and the output state. Its mathematical expression is:

[0127]

[0128] ρ is the density matrix of the input quantum state; ρ′ is the density matrix of the output quantum state.

[0129] After the action of the stratocumulus depolarization channel, the density matrix of the quantum superposition state in QIR has evolved into:

[0130]

[0131] Here, p is the probability that the qubit flips when disturbed by stratocumulus clouds.

[0132] Combining the quantum state throughput rate (1), the quantum state density operator (24) of the depolarized channel, and the fidelity definition (23) can be obtained:

[0133]

[0134] μ aver Combined with equations (21), (22), and (25), we can finally obtain the relationship between the channel survival function and the extinction coefficient after adaptive adjustment.

[0135]

[0136] When the detection distance L is 20km, this application simulates the channel survival function before and after using the photon number adaptive algorithm. The relationship between the channel survival function and the extinction coefficient is as follows: Figure 9 shown.

[0137] From the simulation diagram Figure 9 It can be seen that the larger the extinction coefficient, the smaller the channel survival function. Before and after the algorithm is used, the channel survival function of the system has been significantly improved. Therefore, the QIR system can detect targets in stratus clouds with more water content. LW =0.1034, S cloud Improved from 0.2292 to 0.4167; when the channel survival function S cloud =0, the liquid water content of stratocumulus clouds that the radar system can cope with is improved from 0.1448 to 0.1951.

[0138] This application uses stratocumulus clouds as a backdrop to address the problem of sudden interference from stratocumulus cloud particles due to their water content. We propose an optimal average photon number adaptive adjustment strategy for QIR. Simulations of QIR resolution and channel survival functions, combined with a stratocumulus cloud extinction mathematical model and a depolarization channel, demonstrate the effectiveness of this approach. Simulation results show that the water content of stratocumulus cloud particles significantly attenuates QIR, and that the optimal average photon number adaptive adjustment strategy effectively improves QIR resolution and channel survival functions. Therefore, the proposed approach can effectively improve QIR robustness in the presence of stratocumulus cloud particles with water content.

[0139] It should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like in the above description indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the embodiments of the present disclosure and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the embodiments of the present disclosure.

[0140] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly indicate the number of the technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present disclosure, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0141] In the embodiments of the present disclosure, unless otherwise expressly specified or limited, the terms "installed," "connected," "connected," "fixed," and the like should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integration; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and they may refer to internal communication between two components or interaction between two components. Those skilled in the art will understand the specific meanings of the above terms in the present disclosure based on specific circumstances.

[0142] In the embodiments of the present disclosure, unless otherwise expressly specified and limited, a first feature being "above" or "below" a second feature may include the first and second features being in direct contact, or may include the first and second features being in contact not directly but through another feature between them. Moreover, a first feature being "above," "above," and "above" a second feature includes the first feature being directly above and obliquely above the second feature, or simply indicates that the first feature is higher in level than the second feature. A first feature being "below," "below," and "below" a second feature includes the first feature being directly below and obliquely below the second feature, or simply indicates that the first feature is lower in level than the second feature.

[0143] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification.

[0144] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the appended claims.

Claims

1. An optimal photon number adaptive strategy for quantum interferometer radar under stratocumulus cloud background, characterized by: include: The QIR system generates detection photons and reference photons, both of which have a preset number of photons, and emits the detection photons toward the detection target, while the reference photons remain in the local quantum interferometer radar system; The QIR system receives the reflected detection photons, wherein after the detection photons pass through the stratocumulus cloud, the detection target reflects them back to the QIR system; A mathematical model is established based on the relationship between the reflected detection photons and stratocumulus clouds, and the relationship between the liquid water content of the stratocumulus clouds, the average number of the detection photons, and the transmission distance of the detection photons is obtained; According to the relationship between the liquid water content of the stratocumulus clouds, the average number of detection photons, and the transmission distance of the detection photons, the average number of photons at the radar transmitting end is adaptively adjusted to obtain the optimal average number of photons.

2. The optimal photon number adaptive strategy for quantum interferometer radar under stratocumulus cloud background according to claim 1 is characterized in that: The QIR system includes: Entangled state light source and detection signal processing system.

3. The optimal photon number adaptive strategy for quantum interferometer radar under stratocumulus cloud background according to claim 2 is characterized in that: The steps of generating detection photons and reference photons, both of which have a preset number of photons, by the QIR system and emitting the detection photons toward a detection target include: The entangled state light source generates the preset number of entangled photon pairs, and the entangled photon pairs are split into the detection photons and the reference photons by a beam splitter; The transmitting end of the QIR system emits the detection photons toward the detection target, and the control photons remain in the QIR system as local photons.

4. The optimal photon number adaptive strategy for quantum interferometer radar under stratocumulus cloud background according to claim 1 is characterized in that: The step of establishing a mathematical model based on the reflected detection photons and the reference photons comprises: respectively obtaining the parameters of the reflected detection photons, the parameters of the control photons, and the parameters of the QIR system; The mathematical model is obtained according to the parameters of the reflected detection photons, the parameters of the control photons and the parameters of the QIR system.

5. The optimal photon number adaptive strategy for quantum interferometer radar under stratocumulus cloud background according to claim 4 is characterized in that: The parameters of the reflected detection photons, the parameters of the control photons, and the parameters of the QIR system include at least: The number of photon pulses of the detection photons generated by the QIR system, the probability that the reflected detection photons are detected by the QIR system, the total dark registration rate of the receiving end detector of the QIR system, the probability that the receiving end detector of the QIR system responds, the internal loss of the receiving end detector of the QIR system and the density of the average photon number.

6. The optimal photon number adaptive strategy for quantum interferometer radar under stratocumulus cloud background according to claim 5 is characterized in that: The step of obtaining the mathematical model comprises: Establishing an equation for a pulse photon passing rate based on the number of photon pulses of the detection photons generated by the QIR system, the total dark record rate of the receiving end detector of the QIR system, the probability of the receiving end detector of the QIR system responding, and the density of the average photon number; Obtaining a total transmission rate of the channel under the stratocumulus background based on the internal loss of the receiving detector of the QIR system, the extinction coefficient of the stratocumulus cloud particles, and the transmission distance of the detection photons; Obtaining a pass rate of the photon pulses of the detection photons according to a total transmission rate of the channel under the stratocumulus cloud background and the number of photon pulses of the detection photons generated by the QIR system; Obtaining the probability of a receiving-end detector of the QIR system responding by using the pass rate of the photon pulse of the detection photon and the probability that the reflected detection photon is detected by the QIR system; The mathematical model is obtained based on the equation of the pulse photon pass rate, the total transmission rate of the channel under the stratocumulus cloud background, the pass rate of the photon pulse of the detection photon and the probability of the response of the receiving end detector of the QIR system.

7. The optimal photon number adaptive strategy for quantum interferometer radar under stratocumulus cloud background according to claim 6 is characterized in that: The formula of the mathematical model is: Among them, Q μ is the pulse photon passing rate, μ is the average photon number density, Y0 is the total dark record rate of the receiving detector, η cloud is the total transmission rate of the channel under the stratocumulus background, η det is the internal loss of the detector at the receiving end, k cloud is the extinction coefficient of stratocumulus cloud particles.

8. The optimal photon number adaptive strategy for quantum interference radar under stratocumulus cloud background according to claim 7 is characterized in that: The formula for the optimal average number of photons is: Among them, μ aver is the optimal average number of photons, C LW is the liquid water content of stratocumulus cloud particles, ρ is the density of water, r eff is the effective radius of stratocumulus cloud particles, ed is the detection bit error rate of the detector at the receiving end.

9. The optimal photon number adaptive strategy for quantum interference radar under stratocumulus cloud background according to claim 1 is characterized in that: The steps of enabling the quantum interference radar system to adaptively adjust the average photon number in real time according to the water content of stratus clouds include: If the water content of the stratocumulus cloud particles increases, the average number of photons is increased; If the water content of the stratocumulus cloud particles decreases, then the average number of photons is reduced; If the water content of the stratocumulus cloud particles remains unchanged, the average number of photons remains unchanged.

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