Multi-beam scatterometer for atmosphere and ocean multi-element combined observation

Abstract

The invention discloses a multi-beam scatterometer for atmosphere and ocean multi-element joint observation, which realizes multi-element joint observation by adopting a Ka and Ku wave band double-feed source common reflecting surface system, and comprises an antenna unit, a Ka wave band microwave front end, a Ku wave band microwave front end, a Ka wave band radio frequency receiver, a Ku wave band radio frequency receiver, a Ka wave band transceiving unit and a Ku wave band transceiving unit, and a Ka digital unit and a Ku digital unit. The antenna unit is used for realizing conical scanning of antenna beams through rotation of an antenna reflecting surface, and realizing full coverage of an observation area in a pitching direction by adopting a multi-beam design; the Ka digital unit and the Ku digital unit are used for generating a transmitting signal and a reference pulse signal and controlling the time sequence of a subsystem; signal acquisition and on-satellite processing are realized; multi-beam system joint observation of a sea surface flow field, a wind field and an atmospheric wind field is realized by adopting double PRF signals and an improved radial speed estimation algorithm, and data transmission with a satellite platform is realized.

Description

Technical Field

[0001] The invention relates to a microwave remote sensing instrument, in particular to a multi-beam scatterometer for joint observation of multiple elements of atmosphere and ocean. Background Art

[0002] Momentum is transferred between the atmosphere and the ocean through surface stress, and this "momentum coupling" process depends on the relative motion between the surface flow field and the wind field. The ocean modulates sea surface wind stress through heat flux, etc., and this "thermal coupling" of sea-air interaction depends on the modulation of surface stress by sea surface temperature. Therefore, the joint measurement of sea surface flow velocity, wind speed, and sea surface temperature is crucial for evaluating the role of flow velocity in regulating wind stress and quantifying wind input energy, sea-air interaction, etc., but current ocean observation satellites are unable to provide synchronous observations of the three.

[0003] (1) Although the sea surface height measurement using altimeters (HY-2A, ERS series, Topex-Poseidon, Jason series satellites, etc.) can infer the flow, the inferred flow field only includes the geostrophic flow, not the full flow field. On the other hand, due to the insufficient resolution of the current altimeter, it can only reflect the scale above 100 kilometers and cannot characterize the sub-mesoscale (100 meters-10 kilometers) process;

[0004] (2) Although the Doppler frequency shift measurement or interferometric measurement of SAR (Gaofen-3, ENVISAT, ERS, Sentinel series satellites, etc.) can be used to obtain ocean currents, it is only the radial velocity component, not the vector flow field, and it is difficult to cover the entire world;

[0005] (3) Although SWOT, which is expected to be launched in 2021, can obtain higher resolution (tens of kilometers) observations, it can still only infer geostrophic currents from sea surface heights.

[0006] For atmospheric elements, at a macroscopic scale, there is a lack of observation data on cloud parameters on a global scale, especially in remote areas and ocean regions, where ground-based observation data is missing, and cloud parameters that cannot be obtained by satellite optics become observation gaps. Satellite-borne millimeter-wave radars can observe cloud parameters on a global scale. For example, the CloudSat satellite launched by NASA in 2006 was equipped with the first millimeter-wave cloud radar CPR (Cloud Profiling Radar), which detects the scattering energy of clouds on W-band electromagnetic waves to obtain information such as cloud thickness, cloud height, and cloud amount. Unfortunately, 1) CloudSat adopts a fixed-beam observation method at the nadir point, which can only obtain one line of the subsatellite point cloud and cannot obtain the surface distribution information of clouds within a wide swath; 2) CloudSat only detects the energy information of radar scattering echoes, and does not detect the Doppler frequency shift information that reflects the movement speed of cloud particles. The above two points cause CloudSat to have certain shortcomings in its ability to obtain macro-micro basic parameters of clouds, characterize microphysical processes in clouds, and study the coupling between clouds and weather systems.

[0007] Conducting joint observations of multiple elements of the atmosphere and ocean, and synchronously observing elements such as sea surface wind, sea surface current, and atmospheric wind field, to achieve accurate description and prediction of the ocean system, atmospheric system, and global change processes, is a frontier direction of Earth system science and global change research. Using satellite remote sensing to achieve continuous, stable, and high-resolution observations of the atmosphere and ocean elements on a global scale is of great scientific significance for revealing the multi-scale change process and its dynamic mechanism of the ocean, quantitatively explaining its spatiotemporal change characteristics, evolution laws, biochemical effects, and cross-sphere material and energy exchange, promoting frontier theoretical breakthroughs such as global climate change research, and developing global high-precision forecast models, cloud physics research, weather forecasts, typhoon warnings, climate effect research, and research on earth radiation budget and energy cycle. It is also sufficient to drive the rapid development of multiple disciplines such as oceanography and atmospheric science, marine ecological dynamics, and biogeochemistry. Secondly, by obtaining high-resolution nearshore ocean dynamics data, we can better assess and predict navigation safety, which has important practical significance. Summary of the invention

[0008] The purpose of the present invention is to overcome the defects of the prior art and propose a multi-beam scatterometer for joint observation of multiple elements of the atmosphere and the ocean.

[0009] The present invention proposes a multi-beam scatterometer for joint observation of multiple elements of atmosphere and ocean. The scatterometer adopts a Ka-band and Ku-band dual-feed shared reflection surface system to realize joint observation of multiple elements of atmosphere and ocean, and comprises an antenna unit, a Ka-band microwave front end and a Ku-band microwave front end, a Ka-band radio frequency receiver and a Ku-band radio frequency receiver, a Ka-band transceiver unit and a Ku-band transceiver unit, and a Ka digital unit and a Ku digital unit; wherein,

[0010] The antenna unit is used to realize conical scanning of the antenna beam by rotating the antenna reflective surface, and adopt a multi-beam design to achieve full coverage of the observation area in the pitch direction;

[0011] The Ka-band microwave front end and the Ku-band microwave front end are used to amplify the power of the excitation signal, limit the low-noise amplification of the received signal, and switch the transmitting and receiving channels according to the working sequence of the whole machine;

[0012] The Ka-band radio frequency receiver and the Ku-band radio frequency receiver are used to receive the Ka-band echo signal and the Ku-band echo signal respectively, and send them to the corresponding transceiver unit for further processing;

[0013] The Ka-band transceiver unit and the Ku-band transceiver unit are respectively used to amplify and gain-control the Ka-band echo signal and the Ku-band echo signal, and down-convert the signals to intermediate frequency signals and then send them to the corresponding digital units; up-convert the linear frequency modulation signals generated by the corresponding digital units to radio frequency signals and then send them to the corresponding band microwave front end; and also provide various frequency signals;

[0014] The Ka digital unit and the Ku digital unit are used to generate transmission signals and reference pulse signals, to control the timing of subsystems; to realize signal acquisition and on-board processing functions; to realize multi-beam joint observation of sea surface flow fields, wind fields and atmospheric wind fields by using dual PRF signals and improved radial velocity estimation algorithms, and to transmit data with satellite platforms.

[0015] Preferably, the scatterometer is deployed on a satellite, the orbit of the satellite adopts a sun-synchronous orbit with an orbit altitude of 600 km.

[0016] Preferably, the multi-beam design includes:

[0017] The Ku-band has 3 integrated transmit and receive beams and 3 feed sources, and the Ka-band has 6 groups of 12 independent transmit and receive beams and 12 feed sources.

[0018] Preferably, the antenna unit includes a scanning mechanism and a Ku-band power amplifier and a Ka-band power amplifier, wherein:

[0019] The scanning mechanism is used to complete the driving of the motor and the acquisition of antenna angle data, and the motor adopts an outer rotor motor;

[0020] The Ku-band power amplifier and the Ka-band power amplifier adopt gallium nitride process solid-state power amplifiers, and amplify the transmitted microwave radio frequency pulse signal to the required transmission power by adopting a pulse working mode.

[0021] Preferably, the Ka-band microwave front end and the Ku-band microwave front end both include an electronic switch matrix, a switch drive circuit and a filter.

[0022] Preferably, the various frequency signals provided by the Ka-band transceiver unit and the Ku-band transceiver unit include: a radio frequency local oscillator, an intermediate frequency local oscillator and a clock reference signal required for transceiver of the multi-beam scatterometer.

[0023] Preferably, the Ka digital unit and the Ku digital unit both include a signal and timing generator and a signal processor; wherein,

[0024] The signal and timing generator is used to generate a transmitting Chirp signal and a reference Chirp signal for de-skewing reception, and is also used to generate a system timing signal;

[0025] The signal processor is used to realize signal acquisition and on-board processing, and realizes multi-beam joint observation of sea surface flow field, wind field and atmospheric wind field by adopting dual PRF signals and improved radial velocity estimation algorithm, and is also used to realize data transmission with satellite platform.

[0026] Preferably, the signal processor comprises: a sea surface flow field detection unit, a sea surface wind field detection unit and an atmospheric wind field detection unit, wherein:

[0027] The sea surface flow field detection unit is used to measure Doppler frequency shift by echo pulse interference;

[0028] The sea surface wind field detection unit is used to detect the sea surface wind field by performing multi-angle measurement on the backscattering coefficients at different incident azimuths on the same resolution unit of the sea surface, combined with geophysical model inversion;

[0029] The atmospheric wind field detection unit is used to extract the Doppler frequency shift in the echo signal, and adopts a dual PRF and an improved radial velocity estimation algorithm to realize the calculation of the atmospheric three-dimensional wind field.

[0030] Preferably, the processing process of extracting the Doppler frequency shift in the echo signal by the atmospheric wind field detection unit includes:

[0031] The baseband echo s(t) obtained after down-conversion by the receiver is:

[0032] s(t)=exp(-j2π[f c τ-0.5α(t-τ) 2 ])

[0033] Where t is the echo time within the pulse, 0≤t≤T p ,α is the frequency modulation slope, α=W / T p , T p is the pulse width, W is the signal bandwidth, τ is the echo time shift, fc is the carrier frequency, j represents the imaginary part;

[0034] In every 6 transmitted signals, the first transmitted signal is selected as the reference function s of the matched filtering of the received signals corresponding to the other 5 transmitted signals. ref (t):

[0035] s ref (t) = exp(-j2π[f c τ0-0.5α(t-τ0) 2 ])

[0036] Where τ0 is the reference signal time shift;

[0037] Use FFT to obtain the pulse compression signal s out :

[0038] s out =IFFT{FFT[s(t)]·conj[FFT[s ref (t)]]}

[0039] Take two adjacent pulse compression signals s out1 and out2 , let A = s out1 , B=s out2 , N is the number of related points, then the correlation coefficient ρ(A,B) of adjacent pulse compression signals is:

[0040]

[0041] Among them, μ A , μ B and σ A , σ B , are the mean and standard deviation of A and B respectively, ρ(A,B) is a complex number, and its phase This is the interference phase.

[0042] Preferably, the atmospheric wind field detection unit uses a dual PRF and an improved radial velocity estimation algorithm to calculate the atmospheric three-dimensional wind field, including:

[0043] For the same target speed, the extended Doppler shift is calculated using the phase values ​​at two pulse repetition frequencies;

[0044] For the folded Doppler shift, the phases at the two pulse repetition frequencies are The corresponding folded Doppler shifts are:

[0045]

[0046] Among them, f u1 , fu2 are the maximum unambiguous Doppler shifts under the corresponding pulse repetition intervals, and f1+Mf u1 =f2+Mf u2 =f, M is the number of folding times, f is the actual Doppler frequency shift, let Then f is calculated by the following formula:

[0047]

[0048] in, is the maximum unambiguous Doppler shift after expansion:

[0049] According to Calculate the radial velocity V, where λ is the wavelength of the electromagnetic wave;

[0050] The average wind speed and direction in an area are calculated by the least squares method based on the radial velocity measurements at different azimuths, the radar rotation angle and downward viewing angle measured by the airborne POS;

[0051] make Where θ is the downward viewing angle, is the rotation angle, both are column vectors, then the three-dimensional atmospheric wind field is calculated by the following formula:

[0052]

[0053] Among them, V x , V y , V z are the speeds of the three-dimensional atmospheric wind field in the x, y, and z directions, V radial is the measured radial velocity after unfolding, and p′ represents the transposed matrix of p.

[0054] Compared with the prior art, the advantages of the present invention are:

[0055] 1. The multi-beam scatterometer for joint observation of multiple elements of the atmosphere and ocean will realize the joint observation of multiple elements of the atmosphere and ocean by satellite for the first time, meet the scientific observation requirements of global high-resolution and high-precision sea surface flow field, wind field and atmospheric wind field, realize the overall design of payload and key technologies of Doppler signal on-board processing, high-precision Doppler estimation technology, as well as cloud radar Doppler signal real-time processing algorithm suitable for satellite-borne platform, cloud Doppler three-dimensional velocity vector inversion algorithm and cloud wind guidance algorithm, sea surface Doppler velocity and flow field inversion algorithm, etc.;

[0056] 2. Based on the existing Ku- and Ka-band dual-frequency sea surface flow and wind field measurements, this scatterometer technology proposes an improved multi-beam antenna system. This design overcomes the defects of existing antenna designs and can form fan-shaped beams in the elevation direction to expand the ground coverage of the footprint. It can reduce the antenna rotation speed to below 15rpm, reduce the load complexity required to realize antenna rotation, effectively improve the load life, and achieve full coverage of the observation area in the elevation direction;

[0057] 3. For atmospheric wind field measurement, the improved dual-pulse repetition frequency (PRF) signal form and the improved radial velocity estimation algorithm can achieve a higher maximum unambiguous speed, which is suitable for atmospheric wind field measurement with generally high motion speed. That is, this scatterometer technology can realize the multi-beam system joint observation of multiple elements of the atmosphere and ocean, such as sea surface flow field, wind field and atmospheric wind field for the first time. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a schematic diagram of multi-beam scatterometer observation;

[0059] Figure 2 is a block diagram of the multi-beam scatterometer system;

[0060] Figure 3 It is the specific implementation process of dual PRF in digital unit;

[0061] Figure 4 It is a schematic diagram of wide-swath ocean current and wave detection radar interferometry;

[0062] Figure 5 It is a schematic diagram of target velocity vector observation;

[0063] FIG6 is a diagram of the ocean current observation geometry of a wide swath ocean current and wave detection radar, wherein FIG6(a) is a diagram of the geometric relationship between a single observation scatterometer and a target, and FIG6(b) is a diagram of the scatterometer observing the target twice;

[0064] FIG7 is a schematic diagram of the inversion of the sea surface wind field, wherein FIG7(a) is two observations and FIG7(b) is four observations;

[0065] Figure 8 It is a schematic diagram of the atmospheric wind field velocity folding phenomenon and unwinding method. DETAILED DESCRIPTION

[0066] The present invention proposes a multi-beam scatterometer for joint observation of multiple elements of atmosphere and ocean. The scatterometer adopts a Ka-band and Ku-band dual-feed shared reflection surface system to realize joint observation of multiple elements of atmosphere and ocean, including an antenna unit, a Ka-band microwave front end and a Ku-band microwave front end, a Ka-band radio frequency receiver and a Ku-band radio frequency receiver, a Ka-band transceiver unit and a Ku-band transceiver unit, and a Ka digital unit and a Ku digital unit; wherein,

[0067] The antenna unit is used to realize conical scanning of the antenna beam by rotating the antenna reflective surface, and adopt a multi-beam design to achieve full coverage of the observation area in the pitch direction;

[0068] The Ka-band microwave front end and the Ku-band microwave front end are used to amplify the power of the excitation signal, limit the low-noise amplification of the received signal, and switch the transmitting and receiving channels according to the working sequence of the whole machine;

[0069] The Ka-band radio frequency receiver and the Ku-band radio frequency receiver are used to receive the Ka-band echo signal and the Ku-band echo signal respectively, and send them to the corresponding transceiver unit for further processing;

[0070] The Ka-band transceiver unit and the Ku-band transceiver unit are respectively used to amplify and gain-control the Ka-band echo signal and the Ku-band echo signal, and down-convert the signals to intermediate frequency signals and then send them to the corresponding digital units; up-convert the linear frequency modulation signals generated by the corresponding digital units to radio frequency signals and then send them to the corresponding band microwave front end; and also provide various frequency signals;

[0071] The Ka digital unit and the Ku digital unit are used to generate transmission signals and reference pulse signals, to control the timing of subsystems; to realize signal acquisition and on-board processing functions; to realize multi-beam joint observation of sea surface flow fields, wind fields and atmospheric wind fields by using dual PRF signals and improved radial velocity estimation algorithms, and to transmit data with satellite platforms.

[0072] The technical solution of the present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0073] Example 1

[0074] Embodiment 1 of the present invention proposes a multi-beam scatterometer for joint observation of multiple elements of the atmosphere and ocean.

[0075] In order to achieve wide-swath, high-resolution observations of multiple elements of the atmosphere and ocean, the multi-beam scatterometer is planned to be implemented using a real aperture radar with a dual-frequency (Ka+Ku) conical scanning system. The satellite orbit adopts a sun-synchronous orbit with an orbital altitude of 600km. The Ka-band is part of the microwave band of the electromagnetic spectrum, and the frequency range of the Ka-band is 26.5-40GHz. Ka stands for K-above, in other words, this band is directly above the K-band. The Ka-band is also called the 30 / 20GHz band and is commonly used for satellite communications. The KU band refers to a band with a lower frequency than the K-band under the IEEE 521-2002 standard. The KU band is usually from 10.7 to 12.75GHz for downlink and from 12.75 to 18.1GHz for uplink. The schematic diagram of the multi-beam scatterometer observation is shown below. Figure 1 shown.

[0076] The dual-frequency multi-beam scatterometer scoring system consists of a multi-beam antenna, Ka and Ku band RF receivers, Ka and Ku band microwave front ends, Ka and Ku band transceiver units, Ka and Ku band traveling wave tube amplifiers, Ka and Ku digital units, Ka and Ku power distribution units, scanning mechanisms, servo controllers, waveguide and cable assemblies and other single units. Figure 2 The system principle block diagram and connection diagram are given.

[0077] 1) Radar system

[0078] The multi-beam scatterometer is implemented using a true aperture conical scanning system, including two observation beams of Ku+Ka, and the antenna beam incidence angle is about 48°. The basic working principle of the multi-beam scatterometer is as follows: the microwave transmission channel transmits high-power pulses in the Ku and Ka bands through the antenna through a circulator. After the echo signal scattered by the sea surface is received by the antenna, it is sent to the Ku and Ka polarization receivers respectively through the circulator. After down-conversion and digitization, it is sent to the signal processor, and pulse compression, Doppler frequency estimation and other data processing are completed on the satellite. After achieving a resolution of 5-10km, it is transmitted down through the satellite data transmission subsystem. After calibration, the high-precision backscatter coefficient and Doppler frequency of the observed target are obtained.

[0079] 2) Antenna type

[0080] The antenna of the multi-beam scatterometer adopts a Ku- and Ka-band dual-feed shared reflector system. The feed adopts the offset feed form, and the conical scanning of the antenna beam is realized by rotating the antenna reflector. In order to meet the full coverage of the ground footprint, a multi-beam design is adopted, including 3 beams in the Ku band (3 feeds in the Ku band) and 6 groups of beams in the Ka band (6 groups of Ka band have a total of 12 independent transmit and receive beams, requiring a total of 12 feeds). The multi-beam antenna design overcomes the defects of existing antenna designs and can form fan-shaped beams in the pitch direction to expand the ground coverage of the footprint. The antenna rotation speed can be reduced to less than 15rpm, reducing the load complexity required to realize antenna rotation, effectively improving the load life, and at the same time achieving full coverage of the observation area in the pitch direction.

[0081] 3) Scanning mechanism

[0082] The scanning mechanism unit consists of a motor, a reducer, an angular encoder, and an antenna locking and releasing mechanism. The scanning mechanism unit completes the functions of driving the motor and collecting antenna angle data. The servo motor is designed as an outer rotor motor. The stator and rotor are relatively independent. The main shaft is in the middle of the rotating mechanism, which is both a supporting structure and a load-bearing part for the entire system. The top is equipped with a slip ring, and the middle is a rotary transformer, which can provide the angle information of the antenna rotation. The bottom is the motor and its bearings for support and load-bearing. The lead wires of the motor do not pass through the slip ring to improve the reliability of the system.

[0083] The locking and releasing mechanism locks the antenna during launch, ensures the rigid connection between the antenna components, avoids damage caused by the rotation of the antenna, and supports and protects the rotating shaft. After the satellite enters orbit, the screw is cut off by the pyrotechnic cutter to release the constraint between the antenna and the satellite cabin panel.

[0084] 4) Ku and Ka band power amplifiers

[0085] The Ku and Ka band power amplifiers are planned to use gallium nitride process solid-state power amplifiers and pulse working mode to amplify the transmitted microwave RF pulse signal to the required transmission power.

[0086] 5) Ka and Ku digital units

[0087] The digital unit can be divided into two functional modules: the signal and timing generator and the signal processor, which respectively realize the functions of generating the transmitting and receiving reference pulse signals, controlling the timing of the subsystem, signal acquisition and on-board processing, and data transmission between the subsystem and the platform. The signal and timing generator generates the system timing signal, generates the transmitting Chirp signal and the reference Chirp signal for de-slanted reception; the signal processor realizes the acquisition and processing of remote sensing data and internal telemetry data, and realizes data transmission with the satellite platform. In the atmospheric wind field measurement mode of the multi-beam scatterometer, the use of the dual PRF mode can expand the radial velocity measurement range; after transmitting the first pulse, the second pulse is transmitted at an interval of 200us; after transmitting the second pulse, the third pulse is transmitted at an interval of 250us, and the cycle is repeated in sequence, such as Figure 3 shown.

[0088] 6) Principle of sea surface flow field detection

[0089] The detection of sea surface flow field realizes the measurement of Doppler frequency shift through echo pulse interference. The schematic diagram of the dual-frequency wind wave current scatterometer for interferometric measurement is shown in the figure. Figure 4 As shown. At t = 0, the distance between the radar and the observed target is r (t = 0), and at t = τ, the distance between the radar and the observed target is r (t = τ). The distance difference between the two moments is Δr. The phase difference between the two echo pulses at time 0 and time τ is Δφ. Then:

[0090] Δφ=2kΔr

[0091] Where k is the wave number of the radar electromagnetic wave. The radial velocity component of the observed target can be expressed as:

[0092]

[0093] Using the radial velocity components V of the two observation azimuths r1 and V r2 The velocity vector V of the observed target can be estimated, such as Figure 5 shown.

[0094] The observation geometry of the dual-frequency wind wave current scatterometer when the observation azimuth is φ is shown in Figure 6. The coordinates of point S (microwave scatterometer) are (0, 0, H), and the coordinates of point P (observation target) are The satellite speed is The observed target speed is

[0095] The incident direction vector of the dual-frequency wind-wave-current scatterometer can be expressed as The unit vector of the incident direction is The relative speed (radial speed) between the satellite and the observation point is:

[0096]

[0097] The speed of two targets approaching each other is defined as positive. The Doppler frequency f of the radar echo signal d It can be expressed as

[0098]

[0099] If the time interval between two radar pulse echoes is τ, then the interference phase difference between the two echoes can be expressed as:

[0100]

[0101] Solve for the target speed V x and V y At least two interference phase differences of observation azimuth angles φ1 and φ2 are required, and their corresponding observation azimuth angles are and The solved V x and V y It can be expressed as:

[0102]

[0103]

[0104] The circled position in Figure 7 is the fuzzy solution of the wind field; the simulated wind speed is 10m / s, the wind direction is 80°, Figure 7(a) is two observations, and Figure 7(b) is four observations.

[0105] 7) Principle of sea surface wind field detection

[0106] The principle of wind field measurement by scatterometer is to detect the wind field on the sea surface by multi-angle measurement of the backscatter coefficient at different incident azimuths on the same resolution unit of the sea surface, combined with the inversion of the geophysical model. The following example illustrates the principle of wind field detection and inversion: Assume that the wind speed of the wind unit observed on the sea surface is 10m / s and the wind direction is 80°. When the wind unit is located at the far end of the swath, the antenna is irradiated by the antenna beam at most twice (forward and backward) during the rotation process. Its solution curve is shown in Figure 7(a), and the intersection is the wind speed and wind direction corresponding to the local minimum of the maximum likelihood estimation objective function. The four intersections correspond to four fuzzy solutions, which need to be fuzzy filtered through the attached external wind direction information and wind direction fuzzy removal algorithm. When the wind unit is located in the middle of the swath, it can be irradiated by the antenna beam at most four times, and four observations σ0 at different azimuths are obtained. Its solution curve is shown in Figure 7(b). As can be seen from Figure 7(b), the intersection of the four solution curves is the real sea surface wind field. However, due to the measurement error of the backscatter coefficient, the solution curve will drift, which increases the possibility of generating an erroneous solution, resulting in an ambiguous solution with a 180° direction deviation, as shown in the overlapped part of the solid circle in Figure 7(b). The fuzzy solution of the wind field can be filtered out using the median filter or the Ka-band sea surface Doppler frequency shift information.

[0107] 8) Principle of atmospheric wind field detection

[0108] To calculate the radial Doppler velocity, we need to first extract the Doppler frequency shift in the echo signal measured by the radar. Unlike the detection of sea surface flow fields, the speed of the atmospheric wind field can reach tens of meters per second, which exceeds the maximum unambiguous speed that the pulse pair algorithm can detect, which will produce a folding effect of the radial velocity. For this folded radial velocity, we use a dual pulse repetition frequency (PRF) to measure it. The basic principle is as follows: Figure 8 shown.

[0109] The signal transmitted by the radar is a linear frequency modulated pulse signal, as shown in the following formula:

[0110] s(t)=exp(j2π[ fc t+0.5αt 2 ]), 0≤t≤T p ,α=W / T p

[0111] Among them, f c is the carrier frequency, α is the frequency modulation slope, T p is the pulse width, W is the signal bandwidth, t is the echo time within the pulse, and τ is the echo time shift.

[0112] The radar echo from a point target at R (time delay τ = 2R / c) can be expressed as:

[0113] s(t)=exp(j2π[fc (t-τ)+0.5α(t-τ) 2 ])

[0114] The baseband echo obtained after down-conversion by the receiver:

[0115] s(t)=exp(-j2π[f c τ-0.5α(t-τ) 2 ])

[0116] In every 6 transmitted signals, the first transmitted signal is selected as the reference function of the matched filtering of the received signals corresponding to the other 5 transmitted signals:

[0117] s ref (t) = exp(-j2π[f c τ0-0.5α(t-τ0) 2 ])

[0118] Where τ0 is the reference signal time shift.

[0119] Use FFT to obtain the pulse compression signal:

[0120] s out =IFFT{FFT[s(t)]·conj[FFT[s ref (t)]]}

[0121] Take two adjacent pulse compression signals A = s out1 , B=s out2 , N is the number of related points, then the correlation coefficient of adjacent pulse compression signals is:

[0122]

[0123] where μ A , μ B and σ A , σ B , are the mean and standard deviation of A and B respectively. ρ(A,B) is a complex number, and its phase This is the interference phase.

[0124] For the same target velocity, different pulse repetition intervals will result in different phase values. The phase values ​​at the two pulse repetition frequencies can be used to calculate the expanded radial velocity.

[0125] For the radial velocity after folding, the phases at the two pulse repetition frequencies are: The corresponding radial velocities after folding are: Among them, V u1 , V u2are the maximum unambiguous speeds under the corresponding pulse repetition intervals. And V1+MV u1 =V2+MV u2 =V, M is the number of folds, V is the true speed. The true speed after unfolding can be calculated as follows:

[0126]

[0127] in is the maximum unambiguous speed after expansion:

[0128] Based on the radial velocity measurements at different angles, as well as the radar rotation angle and downward viewing angle measured by the airborne POS, the average wind speed and direction in an area can be calculated using the least squares method.

[0129] Let p = [sin(α)cos(β), sin(α)sin(β), cos(α)], where α is the downward viewing angle and β is the rotation angle, both of which are column vectors. The three-dimensional wind field of the atmosphere can be calculated by the following formula:

[0130]

[0131] Where V radial is the measured radial velocity after unfolding.

[0132] Technical Effects

[0133] The multi-beam scatterometer for joint observation of multiple elements of the atmosphere and ocean adopts a multi-beam rotating scanning observation system. The existing global sea surface flow field is a geostrophic flow obtained by inversion of altimetry satellites, which cannot well describe the small and medium-scale processes in the ocean; the high temporal and spatial resolution sea surface flow field data directly observed by the multi-beam scatterometer will fill the gap in the observation of sub-mesoscale (5-10 kilometers) ocean currents, and the synchronous observation of ocean wind and flow fields will meet the scientific research and observation needs of multi-scale ocean dynamics and its climate impact. At the same time, for the detection of atmospheric elements, the multi-beam scatterometer can obtain cloud scattering intensity and phase information, obtain cloud spatial distribution and Doppler velocity information within a swath greater than 600km, and provide support for the inversion of macro-micro physical parameters such as cloud height, cloud thickness, cloud speed, cloud profile structure, and cloud particle size, motion speed and phase state changes. Using the Doppler information obtained by the spaceborne cloud radar, cloud wind guidance can be further realized to obtain the atmospheric three-dimensional vector wind field under cloud cover conditions, filling the data gap of the missing atmospheric wind field of the spaceborne lidar under non-clear sky conditions.

[0134] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention is described in detail with reference to the embodiments, it should be understood by those skilled in the art that any modification or equivalent replacement of the technical solutions of the present invention does not depart from the spirit and scope of the technical solutions of the present invention and should be included in the scope of the claims of the present invention.

Claims

1. A multi-beam scatterometer for joint observation of multiple elements of atmosphere and ocean, characterized in that: The scatterometer adopts a Ka- and Ku-band dual-feed shared reflector system to realize joint observation of multiple elements of the atmosphere and the ocean, including an antenna unit, a Ka-band microwave front end and a Ku-band microwave front end, a Ka-band radio frequency receiver and a Ku-band radio frequency receiver, a Ka-band transceiver unit and a Ku-band transceiver unit, and a Ka digital unit and a Ku digital unit; wherein, The antenna unit is used to realize conical scanning of the antenna beam by rotating the antenna reflective surface, and adopt a multi-beam design to achieve full coverage of the observation area in the pitch direction; The Ka-band microwave front end and the Ku-band microwave front end are used to amplify the power of the excitation signal, limit the low-noise amplification of the received signal, and switch the transmitting and receiving channels according to the working sequence of the whole machine; The Ka-band radio frequency receiver and the Ku-band radio frequency receiver are used to receive the Ka-band echo signal and the Ku-band echo signal respectively, and send them to the corresponding transceiver unit for further processing; The Ka-band transceiver unit and the Ku-band transceiver unit are respectively used to amplify and gain-control the Ka-band echo signal and the Ku-band echo signal, and down-convert the signals to intermediate frequency signals and then send them to the corresponding digital units; up-convert the linear frequency modulation signals generated by the corresponding digital units to radio frequency signals and then send them to the corresponding band microwave front end; and also provide various frequency signals; The Ka digital unit and the Ku digital unit are used to generate transmission signals and reference pulse signals, to control the timing of subsystems; to realize signal acquisition and on-board processing functions; to realize multi-beam joint observation of sea surface flow fields, wind fields and atmospheric wind fields by using dual PRF signals and improved radial velocity estimation algorithms, and to transmit data with satellite platforms.

2. The multi-beam scatterometer for joint observation of multiple elements of atmosphere and ocean according to claim 1, characterized in that: The scatterometer is deployed on a satellite, the orbit of the satellite adopts a sun-synchronous orbit with an orbit altitude of 600 km.

3. The multi-beam scatterometer for joint observation of multiple elements of atmosphere and ocean according to claim 1, characterized in that: The multi-beam design includes: The Ku-band has 3 integrated transmit and receive beams and 3 feed sources, and the Ka-band has 6 groups of 12 independent transmit and receive beams and 12 feed sources.

4. The multi-beam scatterometer for joint observation of multiple elements of atmosphere and ocean according to claim 1, characterized in that: The antenna unit includes a scanning mechanism and a Ku-band power amplifier and a Ka-band power amplifier, wherein: The scanning mechanism is used to complete the driving of the motor and the acquisition of antenna angle data, and the motor adopts an outer rotor motor; The Ku-band power amplifier and the Ka-band power amplifier adopt gallium nitride process solid-state power amplifiers, and amplify the transmitted microwave radio frequency pulse signal to the required transmission power by adopting a pulse working mode.

5. The multi-beam scatterometer for joint observation of multiple elements of atmosphere and ocean according to claim 1, characterized in that: The Ka-band microwave front end and the Ku-band microwave front end both include an electronic switch matrix, a switch driving circuit and a filter.

6. The multi-beam scatterometer for joint observation of multiple elements of atmosphere and ocean according to claim 1, characterized in that: The various frequency signals provided by the Ka-band transceiver unit and the Ku-band transceiver unit include: radio frequency local oscillator, intermediate frequency local oscillator and clock reference signal required for multi-beam scatterometer transceiver.

7. The multi-beam scatterometer for joint observation of multiple elements of atmosphere and ocean according to claim 1, characterized in that: The Ka digital unit and the Ku digital unit both include a signal and timing generator and a signal processor; wherein, The signal and timing generator is used to generate a transmitting Chirp signal and a reference Chirp signal for de-skewing reception, and is also used to generate a system timing signal; The signal processor is used to realize signal acquisition and on-board processing, and realizes multi-beam joint observation of sea surface flow field, wind field and atmospheric wind field by adopting dual PRF signals and improved radial velocity estimation algorithm, and is also used to realize data transmission with satellite platform.

8. The multi-beam scatterometer for joint observation of multiple elements of atmosphere and ocean according to claim 7, characterized in that: The signal processor includes: a sea surface flow field detection unit, a sea surface wind field detection unit and an atmospheric wind field detection unit, wherein: The sea surface flow field detection unit is used to measure Doppler frequency shift by echo pulse interference; The sea surface wind field detection unit is used to detect the sea surface wind field by performing multi-angle measurement on the backscattering coefficients at different incident azimuths on the same resolution unit of the sea surface, combined with geophysical model inversion; The atmospheric wind field detection unit is used to extract the Doppler frequency shift in the echo signal, and adopts a dual PRF and an improved radial velocity estimation algorithm to realize the calculation of the atmospheric three-dimensional wind field.

9. The multi-beam scatterometer for joint observation of multiple elements of atmosphere and ocean according to claim 6, characterized in that: The processing process of extracting the Doppler frequency shift in the echo signal by the atmospheric wind field detection unit includes: The baseband echo s(t) obtained after down-conversion by the receiver is: s(t)=exp(-j2π[f c τ-0.5α(t-τ) 2 ]) Where t is the echo time within the pulse, 0≤t≤T p , α is the frequency modulation slope, α=W / T p , T p is the pulse width, W is the signal bandwidth, τ is the echo time shift, f c is the carrier frequency, j represents the imaginary part; In every 6 transmitted signals, the first transmitted signal is selected as the reference function s of the matched filtering of the received signals corresponding to the other 5 transmitted signals. ref (t): s ref (t)=exp(-j2π[f c τ0-0.5α(t-τ0) 2 ]) Where τ0 is the reference signal time shift; Use FFT to obtain the pulse compression signal s out : s out =IFFT{FFT[s(t)]·conj[FFT[s ref (t)]]} Take two adjacent pulse compression signals s out1 and out2 , let A = s out1 , B=s out2 , N is the number of related points, then the correlation coefficient ρ(A, B) of adjacent pulse compression signals is: Among them, μ A , μ B and σ A , σ B , are the mean and standard deviation of A and B respectively, ρ(A, B) is a complex number, and its phase This is the interference phase.

10. The multi-beam scatterometer for joint observation of multiple elements of atmosphere and ocean according to claim 9, characterized in that: The atmospheric wind field detection unit adopts dual PRF and improved radial velocity estimation algorithm to realize the calculation of atmospheric three-dimensional wind field, including: For the same target speed, the extended Doppler shift is calculated using the phase values ​​at two pulse repetition frequencies; For the folded Doppler shift, the phases at the two pulse repetition frequencies are The corresponding folded Doppler shifts are: Among them, f u1 , f u2 are the maximum unambiguous Doppler shifts under the corresponding pulse repetition intervals, and f1+Mf u1 =f2+Mf u2 =f, M is the number of folding times, f is the actual Doppler shift, make Then f is calculated by the following formula: in, is the maximum unambiguous Doppler shift after expansion: According to Calculate the radial velocity V, where λ is the wavelength of the electromagnetic wave; The average wind speed and direction in an area are calculated by the least squares method based on the radial velocity measurements at different azimuths, the radar rotation angle and downward viewing angle measured by the airborne POS; make Where θ is the downward viewing angle, is the rotation angle, both are column vectors, then the three-dimensional atmospheric wind field is calculated by the following formula: Among them, V x , V y , V z are the speeds of the three-dimensional atmospheric wind field in the x, y, and z directions, V radial is the measured radial velocity after unfolding, and p′ represents the transposed matrix of p.

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