CN113204019A - Passive high-speed intersection target direct orbit determination method and system - Google Patents
Passive high-speed intersection target direct orbit determination method and system Download PDFInfo
- Publication number
- CN113204019A CN113204019A CN202110293000.5A CN202110293000A CN113204019A CN 113204019 A CN113204019 A CN 113204019A CN 202110293000 A CN202110293000 A CN 202110293000A CN 113204019 A CN113204019 A CN 113204019A
- Authority
- CN
- China
- Prior art keywords
- target
- signal
- rendezvous
- speed
- complex baseband
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 57
- 238000005070 sampling Methods 0.000 claims abstract description 44
- 239000013598 vector Substances 0.000 claims description 36
- 238000012545 processing Methods 0.000 claims description 21
- 230000006870 function Effects 0.000 claims description 15
- 238000004590 computer program Methods 0.000 claims description 11
- 238000003860 storage Methods 0.000 claims description 8
- 230000004044 response Effects 0.000 claims description 6
- 238000004422 calculation algorithm Methods 0.000 abstract description 18
- 238000010586 diagram Methods 0.000 description 22
- 238000004088 simulation Methods 0.000 description 20
- 239000011159 matrix material Substances 0.000 description 10
- 238000004891 communication Methods 0.000 description 6
- 230000008569 process Effects 0.000 description 5
- 239000000126 substance Substances 0.000 description 5
- OAICVXFJPJFONN-UHFFFAOYSA-N Phosphorus Chemical compound [P] OAICVXFJPJFONN-UHFFFAOYSA-N 0.000 description 4
- 238000009795 derivation Methods 0.000 description 4
- 238000005259 measurement Methods 0.000 description 4
- 238000005457 optimization Methods 0.000 description 4
- 238000012360 testing method Methods 0.000 description 4
- 238000007476 Maximum Likelihood Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000009826 distribution Methods 0.000 description 2
- 230000001965 increasing effect Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000012549 training Methods 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- NAWXUBYGYWOOIX-SFHVURJKSA-N (2s)-2-[[4-[2-(2,4-diaminoquinazolin-6-yl)ethyl]benzoyl]amino]-4-methylidenepentanedioic acid Chemical compound C1=CC2=NC(N)=NC(N)=C2C=C1CCC1=CC=C(C(=O)N[C@@H](CC(=C)C(O)=O)C(O)=O)C=C1 NAWXUBYGYWOOIX-SFHVURJKSA-N 0.000 description 1
- 238000000342 Monte Carlo simulation Methods 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000000052 comparative effect Effects 0.000 description 1
- 238000013499 data model Methods 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 238000012942 design verification Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011158 quantitative evaluation Methods 0.000 description 1
- 230000008929 regeneration Effects 0.000 description 1
- 238000011069 regeneration method Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000007493 shaping process Methods 0.000 description 1
- 238000004513 sizing Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/50—Systems of measurement based on relative movement of target
- G01S13/505—Systems of measurement based on relative movement of target using Doppler effect for determining closest range to a target or corresponding time, e.g. miss-distance indicator
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/50—Systems of measurement based on relative movement of target
- G01S13/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
- G01S13/583—Velocity or trajectory determination systems; Sense-of-movement determination systems using transmission of continuous unmodulated waves, amplitude-, frequency-, or phase-modulated waves and based upon the Doppler effect resulting from movement of targets
- G01S13/584—Velocity or trajectory determination systems; Sense-of-movement determination systems using transmission of continuous unmodulated waves, amplitude-, frequency-, or phase-modulated waves and based upon the Doppler effect resulting from movement of targets adapted for simultaneous range and velocity measurements
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Computer Networks & Wireless Communication (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The invention provides a passive high-speed rendezvous target direct orbit determination method and a passive high-speed rendezvous target direct orbit determination system, wherein the method comprises the following steps: obtaining a complex baseband signal in each observation time slot based on a PCM-FM signal transmitted by a telemetering transmitter on a measured target; performing snapshot sampling on the complex baseband signals to obtain a complex baseband discrete sampling sequence in each observation time slot; and acquiring a track parameter estimation result of the detected target according to the complex baseband discrete sampling sequence and the rendezvous target track parameter estimation model. According to the invention, by positioning the track of the high-speed rendezvous target motion, the problem that the traditional algorithm for positioning the target track based on Doppler frequency and phase difference is limited by priori knowledge is solved, and the precision of positioning the target track in a passive high-speed rendezvous scene is improved.
Description
Technical Field
The invention relates to the technical field of target orbit determination, in particular to a passive high-speed intersection target direct orbit determination method and system.
Background
The hit precision of the missile is the primary index for realizing 'point hitting type' accurate hitting, and the realization and the improvement of the missile need to be based on the accurate and quantitative evaluation of a target range test. For this reason, in the target range tests of missile design verification, identification and sizing, production batch inspection and equipment training, the terminal trajectory of the missile relative to a target, namely the vector miss amount, must be measured so as to guide development, assess performance, check quality and evaluate the training level.
An active radar is arranged on a target to directly measure a relative trajectory, so that the method is not limited by range and meteorological conditions, and is the most widely applied technical means for measuring the off-target quantity at present. However, the missile to be measured is a body with a larger geometric size, is not an ideal point scattering source, is limited by factors such as the electromagnetic scattering property of a body target, and the like, and the accuracy is further improved by adopting the vector off-target measurement method of the active radar, so that the accuracy of off-target measurement in a deep sub-meter level is very difficult to realize. Considering that the missile to be tested is usually provided with a telemetering transmitter, the telemetering transmitting signal of the target to be tested can be considered to be passively received, and the signal processing is carried out on the telemetering transmitting signal to realize passive radio vector miss distance measurement. The method can simplify target-mounted equipment, and more importantly, avoids the main restriction factors of the measurement accuracy of the active radar, namely the physical size of the measured target and the electromagnetic scattering property of the target. In addition, the received telemetering signal has high signal-to-noise ratio, so that the measurement accuracy of the vector miss distance can be greatly improved.
In the existing scheme, some research results have appeared for the single-station passive orbit determination problem, and the main idea is to use information such as doppler frequency and Angle Of Arrival (AOA for short) implicit in the received signal to realize the track determination. However, the existing single-station passive orbit determination method is to try to extract intermediate information such as arrival phase difference and pseudo doppler frequency from an observation signal, and then to determine a track by using the relationship between the intermediate information and a track parameter of a target to be measured, and such methods often have the problem that the pseudo doppler frequency is difficult to extract accurately, so that the accuracy of the existing single-station passive orbit determination method is low, and even the method is invalid. Therefore, a passive high-speed rendezvous target direct-tracking method and system are needed to solve the above problems.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a passive high-speed rendezvous target direct orbit determination method and a passive high-speed rendezvous target direct orbit determination system.
The invention provides a passive high-speed rendezvous target direct orbit determination method, which comprises the following steps:
obtaining a complex baseband signal in each observation time slot based on a PCM-FM signal transmitted by a telemetering transmitter on a measured target;
performing snapshot sampling on the complex baseband signals to obtain a complex baseband discrete sampling sequence in each observation time slot;
and acquiring a track parameter estimation result of the detected target according to the complex baseband discrete sampling sequence and the rendezvous target track parameter estimation model.
According to the passive high-speed rendezvous target direct orbit determination method provided by the invention, the complex baseband signal in each observation time slot is obtained based on the PCM-FM signal transmitted by the telemetering transmitter on the target to be detected, and the method comprises the following steps:
acquiring a telemetering receiving array vector signal in each observation time slot according to the PCM-FM signal;
and performing orthogonal receiving processing on the telemetering receiving array vector signal through a nominal telemetering carrier frequency to obtain a complex baseband signal in each observation time slot.
According to the passive high-speed rendezvous target direct orbit determination method provided by the invention, the complex baseband discrete sampling sequence is as follows:
rk＝βkAk(p0,v)sk+nk k＝0,...,K-1；
wherein r iskRepresenting a complex baseband discrete sample sequence, β, in the k-th observation slotkRepresenting the complex propagation coefficient of the arrival of the signal at the observation station in the k-th observation time slot, Ak(p0V) an array response vector, s), representing the arrival of a signal at an observation station in the k-th observation slotkRepresenting the complex envelope of the arrival of the signal at the observation station in the k-th observation time slot, nkRepresenting the observed noise.
According to the passive high-speed rendezvous target direct orbit determination method provided by the invention, the track parameter estimation result of the detected target is obtained according to the complex baseband discrete sampling sequence and the rendezvous target track parameter estimation model, and the method comprises the following steps:
estimating the motion track of the detected target to obtain the estimated track of the detected target;
respectively carrying out grid division on the estimated existence domain of the initial position of the detected target and the estimated existence domain of the speed according to the estimated track through a grid search method, and acquiring a cost function value corresponding to each grid node through the rendezvous target track parameter estimation model;
and taking the track parameter corresponding to the grid node when the value of the cost function value is maximum as the track parameter estimation result of the measured target.
According to the passive high-speed rendezvous target direct orbit determination method provided by the invention, the rendezvous target track parameter estimation model is as follows:
wherein p is0Represents the initial position of the object to be measured, v represents the velocity of the object to be measured,
and K represents the K observation time slot and the total K observation time slots.
According to the invention, the passive high-speed rendezvous target direct orbit determination method further comprises the following steps:
and receiving the PCM-FM signals transmitted by the telemetering transmitter of the object to be measured through a single observation station.
The invention also provides a passive high-speed rendezvous target direct orbit determination system, which comprises:
the signal processing module is used for obtaining a complex baseband signal in each observation time slot based on the PCM-FM signal transmitted by the telemetering transmitter on the target to be detected;
the signal sampling module is used for carrying out snapshot sampling on the complex baseband signals to obtain a complex baseband discrete sampling sequence in each observation time slot;
and the orbit determination module is used for acquiring a track parameter estimation result of the detected target according to the complex baseband discrete sampling sequence and the rendezvous target track parameter estimation model.
According to the invention, the passive high-speed rendezvous target direct orbit determination system provided by the invention comprises the signal processing module and a signal processing module, wherein the signal processing module comprises:
the signal receiving unit is used for acquiring a telemetering receiving array vector signal in each observation time slot according to the PCM-FM signal;
and the signal orthogonal processing unit is used for carrying out orthogonal receiving processing on the telemetering receiving array vector signal through a nominal telemetering carrier frequency to obtain a complex baseband signal in each observation time slot.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the steps of the passive high-speed rendezvous target direct orbit determination method.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the passive high-speed rendezvous target direct tracking method as described in any of the above.
According to the passive high-speed rendezvous target direct orbit determination method and system, the problem that a traditional algorithm for positioning the target track based on Doppler frequency and phase difference is limited by priori knowledge is solved by positioning the track of the motion of the high-speed rendezvous target, and the target track positioning precision in a passive high-speed rendezvous scene is improved.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a passive high-speed rendezvous target direct orbit determination method according to the present invention;
FIG. 2 is a schematic view of an observation scene provided by the present invention;
FIG. 3 is a diagram illustrating the estimation result of the position vector parameters provided by the present invention;
FIG. 4 is a diagram illustrating a velocity vector parameter estimation result provided by the present invention;
FIG. 5 is a diagram illustrating scalar parameter estimation results provided by the present invention;
FIG. 6 is a diagram illustrating a simulation result of a trace according to the present invention;
FIG. 7 is a diagram illustrating a simulation result of a second trajectory provided by the present invention;
FIG. 8 is a diagram illustrating a simulation result of track three provided by the present invention;
FIG. 9 is a diagram illustrating a simulation result of telemetry parameters provided by the present invention;
FIG. 10 is a diagram illustrating a second simulation result of telemetry parameters provided by the present invention;
FIG. 11 is a schematic diagram of a telemetry parameter triple simulation result provided by the present invention;
FIG. 12 is a schematic structural diagram of a passive high-speed intersection target direct tracking system according to the present invention;
fig. 13 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Pulse code modulation-frequency modulation (PCM-FM) telemetry signals are one type of continuous phase modulated signals that exhibit severe doppler frequency variations in high speed crossing scenarios, further enhancing the non-stationary nature of the telemetry received signal. Therefore, the premise of accurately acquiring the pseudo Doppler frequency information hidden in the telemetering receiving signal is that the telemetering parameters of the transmitting end are known in advance, then the receiving end accurately demodulates and reconstructs a local regeneration modulation signal without Doppler frequency, and finally the Doppler frequency information is extracted by using the demodulation result. In practical application, due to the fact that telemetry parameters cannot be completely known, the delay alignment effect in the demodulation reconstruction or demodulation removal process is not ideal, and the Doppler frequency information cannot be accurately extracted, the accuracy of the existing single-station passive orbit determination method based on the Doppler frequency and phase difference information is reduced, and even the existing single-station passive orbit determination method based on the Doppler frequency and phase difference information is invalid. Based on this, the invention provides a Direct tracking method (DTD) for determining a target track by using a single stationary observation station in combination with the idea of Direct positioning. Assuming that the speed and the initial position of the high-speed rendezvous target are unknown, an expected observation signal is reconstructed by constructing a Doppler frequency-phase difference change sequence containing the two unknown parameters, and a least square model is established by combining an actual observation signal, so that the track of the measured target is directly determined. The invention starts from analyzing a PCM-FM observation data model, theoretically deduces an optimization cost function of the DTD and a lower boundary of the Clarmero under the condition of unknown signal waveform.
Fig. 1 is a schematic flow chart of a passive high-speed rendezvous target direct orbit determination method provided by the invention, and as shown in fig. 1, the invention provides a passive high-speed rendezvous target direct orbit determination method, which includes:
and step 101, obtaining a complex baseband signal in each observation time slot based on the PCM-FM signal transmitted by the telemetering transmitter on the measured target.
In the present invention, a PCM-FM signal transmitted by a telemetry transmitter on a target under test is received by a single observation station. FIG. 2 is a schematic view of an observation scene provided by the present invention, as shown in FIG. 2In practical application scenarios, only one static observation station is used for determining the track of the measured target. The arrangement positions of the antenna array elements of the observation station can be referred to as shown in fig. 2, the antenna array elements are clockwise rotated from the upper left corner, the antenna array elements are sequentially marked as antenna array element 1, antenna array element 2 and antenna array element 3, d is the interval of the antenna array elements, and the antenna array element 1 is defined as a reference array element and is positioned at the origin of a coordinate system; marking an included angle between a connecting line between the reference array element and the target and a plane (namely an XOY plane) where the observation station is located as beta; the projection of a connecting line between a reference array element and a target on a plane (XOY plane) where an observation station is located and the positive included angle of the X-axis are marked as alpha; initial position p of rendezvous target (i.e. measured target) at observation zero time0＝[x0 y0 z0]TVelocity v ═ vx vy vz]T. Under the condition of uniform linear motion, the trajectory equation of the measured target is as follows:
pt＝p0+vt； (1)
wherein p istRepresenting the spatial position of the measured object at time t. In the invention, the PCM-FM signal carrier frequency of the measured object telemetering transmitter is fcMaximum modulation frequency offset of Δ fmaxThen at time t, the telemetry transmission signal is:
wherein A iscM (tau) is a signal obtained by pre-modulating and filtering a Pulse Code Modulation (PCM) serial Code through a shaping filter in order to transmit the amplitude of the signal,
is the carrier initial phase.
Further, the obtaining a complex baseband signal in each observation time slot based on the PCM-FM signal transmitted by the telemetry transmitter on the target to be measured specifically includes:
and acquiring the telemetering receiving array vector signal in each observation time slot according to the PCM-FM signal.
In the invention, the telemetering signal is considered to be a plane wave when arriving at the observation station, namely the complex envelopes of the array elements of the observation station, which arrive at the same time, are the same. Through spatial propagation, the telemetering receiving array vector signal of the observation station is as follows:
wherein s isr(t) the telemetering receiving array vector signal of the observation station at the time t, | | | non calculation2Representing the Euclidean norm, betatRepresenting the complex propagation coefficient, alpha, of the signal arriving at the observation station at time tt(p0V) array response vector representing the arrival of a signal at an observation station at time t, ArIn order to receive the amplitude of the signal,
is the initial phase of the received signal;
and the propagation delay of a transmitting signal from a transmitting antenna to a receiving antenna is represented, wherein R (t) is the distance from the telemetering transmitting antenna to the receiving antenna of the observation station, and c is the propagation speed of the electromagnetic wave.
Further, orthogonal receiving processing is carried out on the telemetering receiving array vector signals through a nominal telemetering carrier frequency, and complex baseband signals in each observation time slot are obtained.
In the present invention, a received telemetry receive array vector signal s is received at a nominal telemetry carrier frequencyr(t) performing quadrature reception processing, and obtaining a complex baseband signal represented by:
wherein A isBIs the amplitude of the complex baseband signal and,
is the initial phase of the complex baseband signal; Δ f is the actual telemetry transmission carrier frequency fcWith the local frequency f of the telemetry receiver set by the nominal valuecThe difference between, i.e. Δ f ═ fc-fc′；
Representing the doppler frequency shift caused by radial motion between the target under test and the observation station. In the invention, an observation station is set to observe the rendezvous target for K times, the time length T of an observation time slot is short enough to meet the assumption that the position and the speed of the rendezvous target in a single observation time slot are unchanged, and the complex propagation coefficient beta of a signal reaching the observation station in the kth observation time slotkAnd array response vector alphak(p0V) constant, combining equation (8) and equation (9), the complex baseband signal r in the k-th observation slotk(t) can be expressed as:
pk＝p0+vT(k-1)； (15)
wherein s isk(t) is the complex envelope of the arrival of the signal at the observation station in the k-th observation time slot, pkFor the position of the rendezvous target in the k-th observation time slot, nk(t) is observation noise.
And 102, performing snapshot sampling on the complex baseband signals to obtain a complex baseband discrete sampling sequence in each observation time slot.
In the present invention, if a signal is snapshot-sampled N times in each observation time slot, i.e. the sampling interval
The complex baseband discrete sample sequence in the kth observation slot can be expressed as:
wherein the content of the first and second substances,
the following matrices are now defined:
wherein the content of the first and second substances,
representing the Kronecker product, diag { } represents the vector diagonalization operation, so far, based on equation (17) and equation (18), the complex baseband discrete sample sequence in each observation slot can be represented as:
rk＝βkAk(p0,v)sk+nk k＝0,...,K-1； (19)
wherein r iskRepresenting a complex baseband discrete sample sequence, β, in the k-th observation slotkRepresenting the complex propagation coefficient of the arrival of the signal at the observation station in the k-th observation time slot, Ak(p0V) an array response vector, s), representing the arrival of a signal at an observation station in the k-th observation slotkRepresenting the complex envelope of the arrival of the signal at the observation station in the k-th observation time slot, nkRepresenting the observed noise.
And 103, acquiring a track parameter estimation result of the detected target according to the complex baseband discrete sampling sequence and the rendezvous target track parameter estimation model.
In the present invention, the problem of determining the trajectory of a high-speed rendezvous target can be summarized as how to determine the trajectory from given observation data rk(namely a complex baseband discrete sampling sequence in each observation time slot) directly extracts the track parameter information such as the initial position, the speed and the like of the measured target. Assumed observation noise nkIndependent of the signal, and obeys zero mean Gaussian distribution with power of sigma2Where the maximum likelihood criterion is equivalent to the least squares criterion with respect to the observed quantity rkThe logarithmic form of the maximum likelihood function of (d) is:
the trajectory parameter estimation problem for the rendezvous target can be converted into the following optimization model:
due to betakAnd skThe invention does not contain the track information of the target to be detected, and leads I s to bek||21. When making f1(p0V) maximum, the complex propagation coefficient β is obtainedkLeast squares estimation of
Will be provided with
Substituting equation (20) yields:
since only A is presentk(p0V) contains the position and velocity information of the object to be measured, so let f1(p0V) maximization equivalent to f2(p0V) minimizing:
wherein the content of the first and second substances,
in the present invention, f is the unknown signal waveform2(p0V) maximization equivalent toskMaximization of quadratic form, i.e. the optimization problem of equation (21) can be translated into finding Θk(p0V) maximum eigenvalue problem:
wherein λ ismaxThe operation of taking the maximum characteristic value of the matrix is represented by { }; matrix thetak(p0And v) is an N-dimensional square matrix, and increasing the snapshot number N means that the matrix eigenvalue decomposition calculation amount is increased sharply. To reduce the complexity of the algorithm, consider a given matrix X ∈ CN×1，XXHAnd XHThe non-zero eigenvalues of X are identical, and therefore equation (25) is again equivalent to:
wherein the content of the first and second substances,
in addition, as only one observation station is arranged in the actual scene, the problem of solving complex characteristic values is avoided. Finally, the optimization model for the parameter estimation of the rendezvous target track (i.e. the rendezvous target track parameter estimation model) is:
wherein p is0Represents the initial position of the object to be measured, v represents the velocity of the object to be measured,
and K represents the K observation time slot and the total K observation time slots.
Finally, the present invention utilizes grid searchingMethod, the trajectory parameter { p of the high-speed rendezvous object0V, reasonably dividing the possible existing domain into grids, and respectively calculating the cost function value corresponding to each grid node by combining a formula (27), thereby obtaining the track parameter estimation result
Namely the grid node corresponding to the maximum cost function value.
According to the passive high-speed rendezvous target direct orbit determination method, the problem that a traditional algorithm for positioning the target track based on Doppler frequency and phase difference is limited by priori knowledge is solved by positioning the track of the motion of the high-speed rendezvous target, and the target track positioning precision in a passive high-speed rendezvous scene is improved.
On the basis of the above embodiment, the obtaining a trajectory parameter estimation result of the measured target according to the complex baseband discrete sampling sequence and the rendezvous target trajectory parameter estimation model includes:
and estimating the motion track of the detected target to obtain the estimated track of the detected target.
Respectively carrying out grid division on the estimated existence domain of the initial position of the detected target and the estimated existence domain of the speed according to the estimated track through a grid search method, and acquiring a cost function value corresponding to each grid node through the rendezvous target track parameter estimation model;
and taking the track parameter corresponding to the grid node when the value of the cost function value is maximum as the track parameter estimation result of the measured target.
In the invention, the motion track parameters of the detected target are estimated based on other prior information, a possible existing domain (namely the estimated existing domain) of the initial position and the speed of the detected target is subjected to grid division by combining a grid search method, a cost function value corresponding to each grid point is calculated by using a track parameter estimation model of the intersected target, and finally, the track parameters corresponding to the grid nodes when the value of the cost function is maximum are selected as the track parameter estimation result of the detected target. The specific algorithm flow specifically comprises the following steps:
Step 202, dividing the search grid. Specifically, the trajectory parameter p for the high-speed rendezvous target0V possibly existing domains to reasonably divide the grids, and respectively recording grid nodes consisting of six-dimensional parameters as g1，…gi,…gIAnd let i equal to 1;
step 203, calculating the grid node g by using the formula (9) to the formula (15)iArray response vectors alpha at k-th observation time slots respectivelyk(p0V) and Doppler shift
Step 204, combining the formula (18), the formula (24) and the formula (26), calculating
Step 205, calculating grid node g according to formula (27)iThe objective function value of (1);
step 206, if I is less than I, making I equal to I +1, and returning to execute step 203; otherwise, go to step 207;
step 207, obtain the target function Γ (p)0V) maximum value corresponding to six-dimensional parameters of grid nodes, namely the estimation result of the track parameters of the high-speed intersection target
In order to verify the performance of the algorithm provided by the present invention, in an embodiment, the root mean square error and the Cramer-circle Lower Bound of the 200 monte-chi-fall simulation results of target motion parameter estimation are comparatively given under different signal-to-noise ratios, wherein the derivation process of the Cramer-Rao Lower Bound (CRLB for short) of the target trajectory parameter estimation variance under the gaussian noise distribution condition is specifically:
in combination with equation (17), in the case of an unknown signal waveform, an unknown parameter vector is defined
Wherein:
re (×) and Im (×) represent the real and imaginary part operations, respectively. Therefore, the Fischer Information Matrix (FIM for short) under the observation model of the present invention can be expressed as:
in the invention, observation noise and signals are independent from each other, and the complex envelope s of the signal of each snapshot isk[n]Independent of each other, the complex propagation coefficient beta between observation gapskIndependently of each other, then [ i, j ] th of FIM matrix]The elements are as follows:
wherein [ ] A]iRepresenting the vector [ + ]]The ith element of (1). By block matrix
The derivation process of (a) is as follows:
wherein the content of the first and second substances,
the following can be derived by combining equations (4) to (9) and equations (11) to (16):
for velocity v ═ vx vy vz]TThe derivation process is similar to the equations (a.4) to (a.6), and is not repeated here. In addition, the complex envelope s is processed according to the equations (a.1) to (a.3)k[n]And complex propagation coefficient betakThe partial derivatives are obtained by respectively calculating:
substituting equations (a.3) to (a.7) into equation (a.2) can obtain each element of FIM matrix J, and thus the CRLB lower bound of the target trajectory parameter estimation variance under the observation scenario of the present invention:
wherein [ ] A]lu6The representation is taken as matrix [. X [ ]]The top left 6 main diagonal elements are row vector operations.
After the derivation of the cramer-circle lower bound is completed, further, simulation verification is performed. Signal-to-noise ratio (SNR) of the invention is AB 2/(2σ2) The statistical Root Mean Square Error (RMSE) is defined as:
wherein the true value x ∈ { p ∈ [ ]0V., estimated value of Monte Carlo simulation experiment each time
And C is the simulation times of the Monte Carlo.
The simulation scenario can be referred to as FIG. 2, in which the initial position p of the target is measured0＝[-225 440 315]TThe target speed v is [ 1175-]TRemote sensing carrier fc2.3GHz, carrier offset Δ f 1kHz, sampling frequency
The number of observation gaps K is 7, and the number of snapshots N in each observation gap is 100.
FIG. 3 is a diagram illustrating the estimation result of the position vector parameter, position vector p, according to the present invention0The three-dimensional distance direction estimation root mean square error as a function of the signal to noise ratio can be seen with reference to fig. 3. Fig. 4 is a schematic diagram of the estimation result of the velocity vector parameter provided by the present invention, and reference may be made to fig. 4 for the variation of the root mean square error of the velocity vector v estimation with the signal-to-noise ratio. FIG. 5 is a schematic diagram of the scalar parameter estimation result provided by the present invention, the scalar position distance | | p0||2And scalar velocity | | v | | non-conducting phosphor2The estimated root mean square error varies with the signal to noise ratio, as shown with reference to fig. 5. As can be seen from FIGS. 3-5, when the SNR is less than or equal to-5 dB, the root mean square error of the six-dimensional parameter estimation for target track positioning deviates far from CRLB, indicating that the target track positioning using DPD algorithm is less accurate when the signal-to-noise ratio is low. Generally, the performance of the DPD algorithm gradually approaches to the CRLB along with the increase of the signal-to-noise ratio, and when the SNR is more than or equal to 0dB, the performance of the DPD algorithm is basically consistent with the CRLB.
Further, the miss distance introduced herein by the present invention is defined as the euclidean distance from the intersection of the target trajectory and the observation station plane to the reference array element. In order to verify the applicability of the algorithm, three tracks are respectively given for comparative simulation according to different miss distance and different speed, and the track parameters are shown in table 1:
TABLE 1
| Item | Initial position p0(m) | Velocity vector v (m/s) | Scalar velocity | | v | | non-conducting phosphor2(m/s) | Scalar miss distance (m) |
| Track one | [-135；325；240] | [780；-1400；-1200] | 2002 | 50 |
| Track two | [-200；260；150] | [1120；-800；-600] | 1501 | 100 |
| Track three | [-165；595；345] | [1200；-2250；-1575] | 2997 | 141 |
Other simulation conditions are unchanged, fig. 6 is a schematic diagram of a first simulation result of the trajectory provided by the invention, fig. 7 is a schematic diagram of a second simulation result of the trajectory provided by the invention, fig. 8 is a schematic diagram of a third simulation result of the trajectory provided by the invention, and scalar position distances | p corresponding to different trajectories0||2And scalar velocity | | v | | non-conducting phosphor2Estimated root mean square error statistics, see FIG. 6, respectivelyFig. 7 and 8. Therefore, the CRLB is sensitive to the track parameters, but accurate track parameter estimation can be obtained theoretically only by using the observation data of the intersection section with obvious Doppler frequency change fluctuation for track determination. Meanwhile, under the condition of small signal-to-noise ratio, the estimation accuracy of the algorithm is reduced under the conditions of high speed and large miss distance, and when the SNR is more than or equal to 2dB, the estimation performance of the algorithm is close to the CRLB under the conditions of different miss distances and different speeds, so that the algorithm has good applicability.
Similarly, three sets of telemetry parameters are given according to different telemetry parameters respectively in table 2:
TABLE 2
| Item | Code rate (Mbps) | Frequency offset Δ f (kHz) | Modulation index |
| Remote sensing parameter one | 10 | 1 | 0.7 |
| Remote sensing parameter two | 5 | 10 | 0.3 |
| Telemetering parameter three | 2 | 10 | 0.7 |
The track parameters and other simulation conditions are unchanged, fig. 9 is a schematic diagram of a simulation result of the telemetry parameters provided by the invention, fig. 10 is a schematic diagram of a simulation result of the telemetry parameters provided by the invention, fig. 11 is a schematic diagram of a simulation result of the telemetry parameters provided by the invention, and the distance of scalar positions corresponding to different telemetry parameters | | p0||2And scalar velocity | | v | | non-conducting phosphor2The estimated root mean square error statistics are shown in fig. 9, fig. 10 and fig. 11, respectively. Therefore, the CRLB is insensitive to the telemetering parameters, and meanwhile, when the SNR is larger than or equal to 0dB, the track performance of the algorithm is close to the CRLB for different telemetering parameter conditions, and the robustness is very strong.
The invention provides a combined DPD idea to realize the track positioning of the high-speed intersection target motion and solve the problem that the traditional algorithm for positioning the target track based on Doppler frequency and phase difference is limited by priori knowledge. The CRLB of the target track six-dimensional parameter estimation under the condition of unknown signal waveform is theoretically deduced by combining with the practical engineering problem, and the performance of the algorithm provided by the invention is basically consistent with that of the CRLB under the condition that the SNR is more than or equal to 2dB through simulation verification, so that the algorithm can be used for solving the target track positioning problem under the passive high-speed intersection scene, and a better estimation result can be obtained at the same time.
Fig. 12 is a schematic structural diagram of a passive high-speed rendezvous target direct orbit determination system provided by the invention, and as shown in fig. 12, the passive high-speed rendezvous target direct orbit determination system provided by the invention comprises a signal processing module 1201, a signal sampling module 1202 and an orbit determination module 1203, wherein the signal processing module 1201 is configured to obtain a complex baseband signal in each observation time slot based on a PCM-FM signal transmitted by a telemetry transmitter on a target to be measured; the signal sampling module 1202 is configured to perform snapshot sampling on the complex baseband signal to obtain a complex baseband discrete sampling sequence in each observation time slot; the orbit determination module 1203 is configured to obtain a trajectory parameter estimation result of the target to be measured according to the complex baseband discrete sampling sequence and the rendezvous target trajectory parameter estimation model.
According to the passive high-speed rendezvous target direct orbit determination system, the problem that a traditional algorithm for positioning the target track based on Doppler frequency and phase difference is limited by priori knowledge is solved by positioning the track of the motion of the high-speed rendezvous target, and the target track positioning precision in a passive high-speed rendezvous scene is improved.
On the basis of the above embodiment, the signal processing module includes:
the signal receiving unit is used for acquiring a telemetering receiving array vector signal in each observation time slot according to the PCM-FM signal;
and the signal orthogonal processing unit is used for carrying out orthogonal receiving processing on the telemetering receiving array vector signal through a nominal telemetering carrier frequency to obtain a complex baseband signal in each observation time slot.
The system provided by the embodiment of the present invention is used for executing the above method embodiments, and for details of the process and the details, reference is made to the above embodiments, which are not described herein again.
Fig. 13 is a schematic structural diagram of an electronic device provided in the present invention, and as shown in fig. 13, the electronic device may include: a processor (processor)1301, a communication interface (communication interface)1302, a memory (memory)1303 and a communication bus 1304, wherein the processor 1301, the communication interface 1302 and the memory 1303 complete communication with each other through the communication bus 1304. Processor 1301 may call logic instructions in memory 1303 to perform a passive high-speed rendezvous target direct tracking method, including: obtaining a complex baseband signal in each observation time slot based on a PCM-FM signal transmitted by a telemetering transmitter on a measured target; performing snapshot sampling on the complex baseband signals to obtain a complex baseband discrete sampling sequence in each observation time slot; and acquiring a track parameter estimation result of the detected target according to the complex baseband discrete sampling sequence and the rendezvous target track parameter estimation model.
In addition, the logic instructions in the memory 1303 may be implemented in the form of software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
In another aspect, the present invention also provides a computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, which when executed by a computer, enable the computer to perform the passive high-speed rendezvous target direct tracking method provided by the above methods, the method comprising: obtaining a complex baseband signal in each observation time slot based on a PCM-FM signal transmitted by a telemetering transmitter on a measured target; performing snapshot sampling on the complex baseband signals to obtain a complex baseband discrete sampling sequence in each observation time slot; and acquiring a track parameter estimation result of the detected target according to the complex baseband discrete sampling sequence and the rendezvous target track parameter estimation model.
In yet another aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, the computer program being implemented by a processor to execute the passive high-speed rendezvous target direct tracking method provided in the foregoing embodiments, the method including: obtaining a complex baseband signal in each observation time slot based on a PCM-FM signal transmitted by a telemetering transmitter on a measured target; performing snapshot sampling on the complex baseband signals to obtain a complex baseband discrete sampling sequence in each observation time slot; and acquiring a track parameter estimation result of the detected target according to the complex baseband discrete sampling sequence and the rendezvous target track parameter estimation model.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A passive high-speed rendezvous target direct orbit determination method is characterized by comprising the following steps:
obtaining a complex baseband signal in each observation time slot based on a PCM-FM signal transmitted by a telemetering transmitter on a measured target;
performing snapshot sampling on the complex baseband signals to obtain a complex baseband discrete sampling sequence in each observation time slot;
and acquiring a track parameter estimation result of the detected target according to the complex baseband discrete sampling sequence and the rendezvous target track parameter estimation model.
2. The passive direct tracking method for high-speed rendezvous targets according to claim 1, wherein the obtaining of the complex baseband signal in each observation time slot based on the PCM-FM signal transmitted by the telemetry transmitter on the target to be measured comprises:
acquiring a telemetering receiving array vector signal in each observation time slot according to the PCM-FM signal;
and performing orthogonal receiving processing on the telemetering receiving array vector signal through a nominal telemetering carrier frequency to obtain a complex baseband signal in each observation time slot.
3. The passive high-speed rendezvous target direct-tracking method according to claim 1, wherein the complex baseband discrete sampling sequence is as follows:
rk＝βkAk(p0,v)sk+nk k＝0,...,K-1；
wherein r iskRepresenting a complex baseband discrete sample sequence, β, in the k-th observation slotkRepresenting the complex propagation coefficient of the arrival of the signal at the observation station in the k-th observation time slot, Ak(p0V) an array response vector, s), representing the arrival of a signal at an observation station in the k-th observation slotkRepresenting the complex envelope of the arrival of the signal at the observation station in the k-th observation time slot, nkRepresenting the observed noise.
4. The passive high-speed rendezvous target direct orbit determination method according to claim 1, wherein the obtaining of the trajectory parameter estimation result of the target to be measured according to the complex baseband discrete sampling sequence and the rendezvous target trajectory parameter estimation model comprises:
estimating the motion track of the detected target to obtain the estimated track of the detected target;
respectively carrying out grid division on the estimated existence domain of the initial position of the detected target and the estimated existence domain of the speed according to the estimated track through a grid search method, and acquiring a cost function value corresponding to each grid node through the rendezvous target track parameter estimation model;
and taking the track parameter corresponding to the grid node when the value of the cost function value is maximum as the track parameter estimation result of the measured target.
5. The passive high-speed rendezvous target direct orbit determination method according to claim 4, wherein the rendezvous target trajectory parameter estimation model is as follows:
wherein p is0Represents the initial position of the object to be measured, v represents the velocity of the object to be measured,
and K represents the K observation time slot and the total K observation time slots.
6. The passive high-speed rendezvous target direct-tracking method according to claim 1, further comprising:
and receiving the PCM-FM signals transmitted by the telemetering transmitter of the object to be measured through a single observation station.
7. A passive high-speed rendezvous target direct tracking system, comprising:
the signal processing module is used for obtaining a complex baseband signal in each observation time slot based on the PCM-FM signal transmitted by the telemetering transmitter on the target to be detected;
the signal sampling module is used for carrying out snapshot sampling on the complex baseband signals to obtain a complex baseband discrete sampling sequence in each observation time slot;
and the orbit determination module is used for acquiring a track parameter estimation result of the detected target according to the complex baseband discrete sampling sequence and the rendezvous target track parameter estimation model.
8. The passive high-speed rendezvous target direct tracking system according to claim 7, wherein the signal processing module comprises:
the signal receiving unit is used for acquiring a telemetering receiving array vector signal in each observation time slot according to the PCM-FM signal;
and the signal orthogonal processing unit is used for carrying out orthogonal receiving processing on the telemetering receiving array vector signal through a nominal telemetering carrier frequency to obtain a complex baseband signal in each observation time slot.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the computer program implements the steps of the passive high-speed rendezvous target direct orbit determination method according to any one of claims 1 to 6.
10. A non-transitory computer readable storage medium having a computer program stored thereon, wherein the computer program when executed by a processor implements the steps of the passive high speed rendezvous target direct tracking method according to any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110293000.5A CN113204019B (en) | 2021-03-18 | 2021-03-18 | Passive high-speed intersection target direct orbit determination method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110293000.5A CN113204019B (en) | 2021-03-18 | 2021-03-18 | Passive high-speed intersection target direct orbit determination method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113204019A true CN113204019A (en) | 2021-08-03 |
| CN113204019B CN113204019B (en) | 2024-02-27 |
Family
ID=77025489
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110293000.5A Active CN113204019B (en) | 2021-03-18 | 2021-03-18 | Passive high-speed intersection target direct orbit determination method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113204019B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030197644A1 (en) * | 2001-12-14 | 2003-10-23 | Stephane Paquelet | Method for passive localization of a target and air-air localization in particular |
| CN106507953B (en) * | 2006-05-12 | 2012-03-07 | 中国科学院国家天文台 | The passive Orbit determination of satellite and system |
| CN104270713A (en) * | 2014-09-09 | 2015-01-07 | 西北大学 | Passive type moving target track mapping method based on compressed sensing |
| CN209462366U (en) * | 2019-02-18 | 2019-10-01 | 西安汉华防务电子科技有限公司 | A kind of telemetering digital if receiver |
| CN110297234A (en) * | 2018-03-22 | 2019-10-01 | 西安航通测控技术有限责任公司 | A kind of big region passive type air target intersection measuring method of networking and system |
-
2021
- 2021-03-18 CN CN202110293000.5A patent/CN113204019B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030197644A1 (en) * | 2001-12-14 | 2003-10-23 | Stephane Paquelet | Method for passive localization of a target and air-air localization in particular |
| CN106507953B (en) * | 2006-05-12 | 2012-03-07 | 中国科学院国家天文台 | The passive Orbit determination of satellite and system |
| CN104270713A (en) * | 2014-09-09 | 2015-01-07 | 西北大学 | Passive type moving target track mapping method based on compressed sensing |
| CN110297234A (en) * | 2018-03-22 | 2019-10-01 | 西安航通测控技术有限责任公司 | A kind of big region passive type air target intersection measuring method of networking and system |
| CN209462366U (en) * | 2019-02-18 | 2019-10-01 | 西安汉华防务电子科技有限公司 | A kind of telemetering digital if receiver |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113204019B (en) | 2024-02-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110493742B (en) | Indoor three-dimensional positioning method for ultra-wideband | |
| CN109752710B (en) | Rapid target angle estimation method based on sparse Bayesian learning | |
| CN106851821B (en) | Indoor three-dimensional positioning method based on wireless communication base station | |
| EP2656101B1 (en) | Target altitude estimation based on measurements obtained by means of a passive radar | |
| US9213100B1 (en) | Bearing-only tracking for horizontal linear arrays with rapid, accurate initiation and a robust track accuracy threshold | |
| CN106610483A (en) | MIMO radar angle estimation algorithm based on tensor space and spectral peak search | |
| CN110210067B (en) | Method and device for determining threshold straight line based on measurement track | |
| CN108957387A (en) | A kind of satellite-signal two-dimentional angle estimation method and system | |
| CN112162244B (en) | Event trigger target tracking method under related noise and random packet loss environment | |
| Meissner et al. | Analysis of position-related information in measured UWB indoor channels | |
| CN106772302A (en) | A kind of knowledge assistance STAP detection methods under complex Gaussian background | |
| CN110098882A (en) | Multiple antennas broadband frequency spectrum detection method based on compressed sensing and entropy | |
| Arsan et al. | A Clustering‐Based Approach for Improving the Accuracy of UWB Sensor‐Based Indoor Positioning System | |
| Hamdollahzadeh et al. | Moving target localization in bistatic forward scatter radars: Performance study and efficient estimators | |
| CN106154241B (en) | Tough parallel factorial analysis algorithm under impulse noise environment | |
| CN107592654B (en) | Method for positioning field intensity of same-frequency multiple radiation sources based on compressed sensing | |
| CN109521418A (en) | Ground-based radar angle-measuring method based on interference field | |
| CN108490465A (en) | Based on when frequency difference and direction finding ground with doing more physical exercises frequently radiation source tracking and system | |
| CN113204019A (en) | Passive high-speed intersection target direct orbit determination method and system | |
| Wielandner et al. | Multipath-based SLAM with multiple-measurement data association | |
| CN112213697A (en) | Feature fusion method for radar deception jamming recognition based on Bayesian decision theory | |
| Liu et al. | GNSS multi-interference source centroid location based on clustering centroid convergence | |
| Huiting et al. | Near field phased array DOA and range estimation of UHF RFID tags | |
| Li et al. | Robust kernel-based machine learning localization using NLOS TOAs or TDOAs | |
| CN114548159B (en) | Ultra-wideband accurate positioning method under signal interference |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |