CN111812612A - Partial correlation waveform design method of MIMO radar based on subarray orthogonal LFM signal - Google Patents
Partial correlation waveform design method of MIMO radar based on subarray orthogonal LFM signal Download PDFInfo
- Publication number
- CN111812612A CN111812612A CN202010559445.9A CN202010559445A CN111812612A CN 111812612 A CN111812612 A CN 111812612A CN 202010559445 A CN202010559445 A CN 202010559445A CN 111812612 A CN111812612 A CN 111812612A
- Authority
- CN
- China
- Prior art keywords
- sub
- array
- signal waveform
- lfm signal
- lfm
- 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 68
- 238000013461 design Methods 0.000 title claims abstract description 18
- 238000003491 array Methods 0.000 claims abstract description 21
- 230000015572 biosynthetic process Effects 0.000 claims abstract description 14
- 238000003786 synthesis reaction Methods 0.000 claims abstract description 14
- 238000012545 processing Methods 0.000 claims abstract description 13
- 239000013598 vector Substances 0.000 claims description 26
- 238000005070 sampling Methods 0.000 claims description 24
- 239000011159 matrix material Substances 0.000 claims description 22
- 238000005457 optimization Methods 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 4
- 238000004088 simulation Methods 0.000 description 27
- 230000005540 biological transmission Effects 0.000 description 8
- 230000010354 integration Effects 0.000 description 4
- 238000007796 conventional method Methods 0.000 description 3
- 238000001514 detection method Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000006835 compression Effects 0.000 description 1
- 238000007906 compression Methods 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 230000035945 sensitivity 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
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/42—Diversity systems specially adapted for radar
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 discloses a partial correlation waveform design method of an MIMO radar based on a subarray orthogonal LFM signal, which comprises the following steps: establishing an MIMO radar model; the MIMO radar model comprises a plurality of transmitting sub-arrays; acquiring an LFM signal waveform of each sub-array; processing the LFM signal waveform of each subarray to obtain a pulse comprehensive result; constructing a cost function according to the sidelobe amplitude of the pulse synthesis result; and optimizing the LFM signal waveform of each sub-array by using the cost function to obtain the final LFM signal waveform of the sub-array. Due to the particularity of the subarray structure, independent constraint on the emission energy coverage map is not needed, so that the waveform is easy to generate, and the matching degree of the emission energy coverage map is good; in addition, the invention ensures that the pulse synthesis result of each angle in the expected direction has lower side lobe by optimizing the signal bandwidth and the initial phase, and the main lobe is not widened.
Description
Technical Field
The invention belongs to the technical field of radars, and particularly relates to a partial correlation waveform design method of an MIMO radar based on a subarray orthogonal LFM signal.
Background
In recent years, a Multiple Input Multiple Output (MIMO) radar has attracted a wide interest and attention in the field of array signal processing as a new type of radar. The MIMO radar is divided into a distributed type and a centralized type, wherein the centralized type transceiving antenna is short in distance, each array element can transmit different waveforms, and the MIMO radar has the advantage of waveform diversity. Compared with a phased array radar, the method has higher degree of freedom, can obtain higher angular resolution, and has better parameter discrimination capability and anti-interception capability. The transmission degrees of freedom of the MIMO radar are concentrated in the MIMO radar transmission waveform. Therefore, the method has important significance for researching the waveform with higher degree of freedom, improving the system performance, increasing the system flexibility and improving the system adaptability.
The MIMO radar can adjust the transmitting waveform according to a specific working mode so as to reasonably distribute the transmitting energy and has higher flexibility. According to different working modes, the transmitted waveform can be divided into an orthogonal waveform, a partial correlation waveform and the like, wherein the partial correlation waveform is between the orthogonal waveform and the traditional phased array radar, the transmitted energy only covers the area to be observed, and compared with the orthogonal waveform, the energy utilization rate of the radar and the signal-to-noise ratio of an echo signal are improved, so that the target detection and parameter estimation are facilitated. LFM (Linear Frequency Modulation) signals are widely used as radar transmission waveform signals because they have a lower degree of freedom in design, have good doppler tolerance, and are easy to generate in practical applications, compared with phase-encoded signals.
Currently, the prior art proposes two methods for generating LFM waveforms: one is to realize the design of the single-beam emission energy coverage map by optimizing equal frequency intervals and initial phases with fixed difference. The method can directly obtain the transmitted waveform, the obtained partial related LFM waveform has better transmitted energy coverage map matching performance, the pulse comprehensive result has lower side lobe, but the main lobe of the pulse comprehensive result is widened greatly, and the range resolution of a radar system is seriously influenced. Secondly, the side lobe of pulse synthesis is reduced as much as possible under the condition that the error between the waveform transmitted energy coverage map and the expected transmitted energy coverage map is in a set range by adjusting the frequency interval and the initial phase of each signal. The partial correlation LFM waveform designed by the method has better transmitted energy coverage map matching performance, the main lobe of the pulse synthesis result is not widened, but the pulse synthesis result of each angle in an expected direction cannot be ensured to have lower side lobes, and the detection performance of a radar system can be influenced.
Disclosure of Invention
In order to solve the above problems in the prior art, the present invention provides a partial correlation waveform design method for MIMO radar based on orthogonal LFM signals of subarrays. The technical problem to be solved by the invention is realized by the following technical scheme:
a partial correlation waveform design method of a MIMO radar based on a subarray orthogonal LFM signal comprises the following steps:
establishing an MIMO radar model; the MIMO radar model comprises a plurality of transmitting sub-arrays;
acquiring an LFM signal waveform of each sub-array;
obtaining a pulse comprehensive result according to the LFM signal waveform of each sub-array;
constructing a cost function according to the sidelobe amplitude of the pulse synthesis result;
and optimizing each sub-array LFM signal waveform by using the cost function to obtain a final sub-array LFM signal waveform.
In an embodiment of the present invention, the expression of the LFM signal waveform of the sub-array is:
wherein s iskLFM signal waveform representing the kth sub-array, k being 1,2,3, …, M1，M1Representing the number of sub-arrays, fkCenter frequency, mu, of waveform of LFM signal representing kth sub-arraykIndicates the chirp rate of the LFM signal waveform of the k-th sub-array, and muk＝Bk/Te，TeRepresents the pulse width of radar emission signal, and T represents 0-TeInternal sample time, BkThe signal bandwidth of the LFM signal waveform representing the kth sub-array,
indicating the initial phase of the LFM signal waveform for the kth sub-array.
In one embodiment of the present invention, obtaining a pulse synthesis result according to the LFM signal waveform of each of the sub-arrays includes:
obtaining LFM signal waveform matrixes of a plurality of sub-arrays according to the LFM signal waveform of each sub-array;
forming the LFM signal waveform matrix of the sub-array into a total LFM signal waveform matrix of the whole transmitting array;
and processing the total LFM signal waveform matrix to obtain a pulse comprehensive result.
In an embodiment of the present invention, processing the total LFM signal waveform matrix to obtain a pulse synthesis result includes:
discretely and uniformly taking P sampling angles in a range of-3 dB of an expected emission energy coverage map, and calculating a guide vector of each sampling angle;
obtaining an echo signal according to the steering vector of the sampling angle and the total LFM signal waveform matrix;
and carrying out pulse comprehensive processing on the echo signals to obtain a pulse comprehensive result.
In an embodiment of the present invention, the calculation formula of the steering vector of the sampling angle is:
a(θp)＝[1 exp(j2πdsinθp/λ)…exp(j(M-1)2πdsinθp/λ)]T；
wherein, a (theta)p) Representing the sampling angle thetapP is 1,2, …, P, and the sampling angle θpSatisfies theta1＜θ2＜…＜θPM represents the total number of the transmitting array elements, d represents the transmitting array element spacing, and lambda represents the wavelength of the radar transmitting signal]TRepresenting a transpose operation.
In an embodiment of the present invention, the expression of the pulse integration result is:
y(θp,l)＝xcorr(sr)＝xcorr(a(θp)TS)；
wherein l represents-Te～TeThe sampling time of the inner 2L-1 point, L is 0 to TeTotal number of sampling times in xcorr (·) denotes an autocorrelation operation, sr denotes an echo signal, and sr ═ a (θ)p)TS, S represents the total LFM signal waveform matrix.
In an embodiment of the present invention, the expression of the cost function is:
wherein, BkSignal bandwidth representation of the waveform of the LFM signal representing the kth sub-array, BminAnd BmaxRespectively represent BkThe upper limit value and the lower limit value of (c),
the initial phase of the LFM signal waveform representing the kth sub-array,
M1indicating the number of sub-arrays.
In an embodiment of the present invention, optimizing the LFM signal waveform of each sub-array by using the cost function to obtain a final LFM signal waveform of the sub-array includes:
respectively optimizing the signal bandwidth of the LFM signal waveform of each sub-array and the initial phase of the LFM signal waveform of each sub-array according to the cost function to obtain the optimized signal bandwidth and the optimized initial phase;
obtaining an optimized frequency modulation slope according to the optimized signal bandwidth;
and obtaining a final sub-array LFM signal waveform according to the optimized frequency modulation slope and the optimized initial phase.
In an embodiment of the present invention, optimizing the signal bandwidth of the LFM signal waveform of each of the sub-arrays and the initial phase of the LFM signal waveform of each of the sub-arrays according to the cost function respectively to obtain an optimized signal bandwidth and an optimized initial phase includes:
will M1B isminAnd M10 s form a first column vector, and M is added1B ismaxAnd M12 pi component column vectors are second column vectors;
introducing an fminimax function, taking the cost function as a function of the fminimax function, taking a signal bandwidth of an LFM signal waveform of the sub-array and an initial phase of the LFM signal waveform of the sub-array as input variables of the fminimax function, taking the first column vector as a lower input variable limit of the fminimax function, and taking the second column vector as an upper input variable limit of the fminimax function;
and calling the fminimax function to optimize the signal bandwidth of the LFM signal waveform of each sub-array and the initial phase of the LFM signal waveform of each sub-array to obtain the optimized signal bandwidth and the optimized initial phase.
In an embodiment of the present invention, the expression of the final sub-array LFM signal waveform is:
wherein s isk' represents the optimized LFM signal waveform of the kth sub-array, fkDenotes the center frequency, μ 'of the LFM signal waveform of the k-th sub-matrix'kIndicates the chirp rate, T, of the kth subarray optimizationeRepresents the pulse width of the radar transmission signal,
indicating the initial phase of the kth subarray optimization.
The invention has the beneficial effects that:
1. the partial correlation waveform design method of the MIMO radar adopts the subarray structure, and due to the particularity of the subarray structure, independent constraint on the emission energy coverage map is not needed, so that the waveform is easy to generate, and the matching degree of the emission energy coverage map is good;
2. the related waveform design method of the MIMO radar part enables the comprehensive result of the pulse of each angle in the expected direction to have lower side lobes and the main lobe not to be widened by optimizing the signal bandwidth.
The present invention will be described in further detail with reference to the accompanying drawings and examples.
Drawings
Fig. 1 is a schematic diagram of a partial correlation waveform design method of a MIMO radar based on orthogonal LFM signals of a sub-array according to an embodiment of the present invention;
FIG. 2 is a comparison graph of waveform emission energy coverage of a prior art method and a method of the present invention under simulation conditions;
FIG. 3 is a comparison graph of waveforms of the prior art method and the proposed method under simulation conditions for a-5 clock integration according to the present invention;
FIG. 4 is a comparison graph of waveforms of the prior art method and the proposed method under simulation conditions, which are integrated at 0 degrees according to the present invention;
FIG. 5 is a comparison graph of waveforms of the prior art method and the proposed method under simulation conditions, which are integrated at 5 degrees;
FIG. 6 is a comparison graph of waveform emission energy coverage of the prior art method and the proposed method under the second simulation condition provided by the embodiment of the present invention;
FIG. 7 is a comparison graph of waveforms of the prior art method and the method of the present invention under the second simulation condition, which are integrated at 20 degrees.
Detailed Description
The present invention will be described in further detail with reference to specific examples, but the embodiments of the present invention are not limited thereto.
Example one
Referring to fig. 1, fig. 1 is a schematic diagram of a partial correlation waveform design method for a MIMO radar based on orthogonal LFM signals of a subarray according to an embodiment of the present invention, which includes:
step 1: establishing an MIMO radar model; the MIMO radar model comprises a plurality of transmitting sub-arrays.
Specifically, setting the MIMO radar model includes M1The number of the array elements of each sub-array is determined to be M according to the-3 dB width of the expected emission energy coverage map2If the total number of the transmitting array elements is M, and M is equal to M1M2。
The M array elements are arranged in a straight line, the spacing of the array elements is equal, a transmitting array of the MIMO radar is formed, all the array elements in the sub-array transmit the same LFM signals, the beam direction (namely the central direction of a transmitting energy coverage map) can be controlled by changing the initial phase of each signal in the sub-array, and the sub-arrays are mutually orthogonal signals.
Initializing various parameters of the radar model, and setting the pulse width of a radar emission signal to be TeL is 0 to TeThe total number of sampling time in the array, the frequency interval of the signals between the sub-arrays is delta f, and the delta f is 1/Te。
Setting the center frequency of the LFM signal waveform of the kth sub-array to be fk，fk＝f0+CmΔ f, wherein f0Is a carrier frequency, CmIs frequency coded, and Cm＝0,1,2,...,M1-1，k＝1,2,3,…,M1Simultaneously setting the initial phase of the LFM signal waveform of the kth sub-array
Are each set to a random value in the range of [0,2 π),
setting the signal bandwidth of the LFM signal waveform of the kth sub-array to be BkAnd determining BkHas an upper limit of BmaxThen determining the lower limit B according to the result of Doppler sensitivity of signals with different bandwidth lower limitsmin(ii) a In [ B ]min,Bmax]Within a range of randomly generating M1Values, respectively given to Bk，k＝1,2,3,…,M1。
Step 2: the LFM signal waveform for each sub-array is acquired.
First, according to the signal bandwidth BkAnd the pulse width T of the individual signalseCalculating the chirp slope mukThe calculation formula is muk＝Bk/Te；
Then, according to the center frequency fkFrequency modulation slope mukAnd initial phase
Obtaining LFM signal waveform skThe expression is as follows:
wherein s iskLFM signal waveform representing the kth sub-array, k being 1,2,3, …, M1，M1Representing the number of sub-arrays, fkCenter frequency, mu, of waveform of LFM signal representing kth sub-arraykIndicates the chirp rate of the LFM signal waveform of the k-th sub-array, and muk＝Bk/Te，TeRepresents the pulse width of radar emission signal, and T represents 0-TeInternal sample time, BkThe signal bandwidth of the LFM signal waveform representing the kth sub-array,
indicating the initial phase of the LFM signal waveform for the kth sub-array.
And step 3: and processing the LFM signal waveform of each sub-array to obtain a pulse comprehensive result.
31) And obtaining the LFM signal waveform matrixes of a plurality of sub-arrays according to the LFM signal waveform of each sub-array.
Specifically, each sub-array LFM signal waveform skForm each subarray signal waveform matrix Sk＝[sk；...；sk]Wherein S iskComprising M2S isk。
32) And forming the LFM signal waveform matrixes of the sub-matrixes into a total LFM signal waveform matrix of the whole transmitting array.
Specifically, the signal waveform matrix S of each subarraykLFM signal waveform matrix forming the whole transmitting array assembly
33) Processing the total LFM signal waveform matrix to obtain a pulse comprehensive result, which specifically comprises the following steps:
33-1) taking P sampling angles discretely and uniformly within-3 dB of the desired transmit energy coverage map, and calculating a steering vector for each sampling angle.
Specifically, the values of P points are discretely and uniformly taken within the range of-3 dB of the expected emission energy coverage map and are arranged from small to large as [ theta ]1,…,θp,…,θP]Obtaining a sampling angle theta according to the spacing d of the transmitting array elements and the wavelength lambda of a radar transmitting signalpThe steering vector of (a) is:
a(θp)＝[1 exp(j2πdsinθp/λ)…exp(j(M-1)2πdsinθp/λ)]T；
wherein, a (theta)p) Representing the sampling angle thetapP is 1,2, …, P, and the sampling angle θpSatisfies theta1＜θ2＜…＜θPM represents the total number of the transmitting array elements, d represents the transmitting array element spacing, and lambda represents the wavelength of the radar transmitting signal]TRepresenting a transpose operation.
33-2) obtaining an echo signal according to the steering vector of the sampling angle and the total LFM signal waveform matrix.
Specifically, the expression of the echo signal sr is sr ═ a (θ)p)TS, wherein S represents the total LFM signal waveform matrix.
33-3) carrying out pulse comprehensive processing on the echo signals to obtain a pulse comprehensive result.
Specifically, the pulse integration result y (θ)pAnd l) is expressed as:
y(θp,l)＝xcorr(sr)＝xcorr(a(θp)TS)；
wherein l represents-Te～TeThe sampling time of the inner 2L-1 point, L is 0 to TeThe total number of sample times within, xcorr (·), represents the autocorrelation operation.
And 4, step 4: and constructing a cost function according to the sidelobe amplitude waveform of the pulse synthesis result.
Specifically, the processed signal y (θ) is synthesized from the pulsespL), the following cost function model is established:
wherein J represents a cost function,
and 5: and optimizing each sub-array LFM signal waveform by using the cost function to obtain the final sub-array LFM signal waveform.
51) Optimizing the signal bandwidth of the LFM signal waveform of each sub-array and the initial phase of the LFM signal waveform of each sub-array according to the cost function to obtain an optimized signal bandwidth and an optimized initial phase, specifically comprising:
51-1) adding M1B isminAnd M10 s form a first column vector, and M is added1B ismaxAnd M12 pi component column vectors are second column vectors;
specifically, M is1B isminAnd M 10's form a first column vector B, whose expression B ═ Bmin,…Bmin,0,…,0]TAt the same time, M1B ismaxAnd M1Each 2 pi forms a second column vector c, whose expression is c ═ Bmax,…Bmax,2π…,2π]T。
51-2) introducing an fminimax function, taking a cost function J as a function of the fminimax function, and taking a signal bandwidth B of an LFM signal waveform of the subarraykInitial phase of LFM signal waveform of sum sub-array
As input variables of the fminimax function, the first column vector b is taken as the lower limit of the input variables of the fminimax function, and the second column vector c is taken as the lower limit of the input variables of the fminimax functionAn upper limit of an input variable that is a fminimax function; thereby converting the mathematical model of the cost function in step 4 into a form that fminimax can call.
51-3) calling an fminimax function to optimize the signal bandwidth of the LFM signal waveform of each sub-array and the initial phase of the LFM signal waveform of each sub-array, so as to obtain the optimized signal bandwidth and the optimized initial phase.
Specifically, the fminimax function is called to carry out the signal bandwidth B on each subarray waveformkInitial phase of
Optimizing to obtain optimized signal bandwidth Bk' and optimized initial phase
52) And obtaining the optimized frequency modulation slope according to the optimized signal bandwidth.
Specifically, the calculation formula of the optimized chirp rate is as follows: mu.sk′＝Bk′/T。
53) And obtaining the final sub-array LFM signal waveform according to the optimized frequency modulation slope and the optimized initial phase.
In particular, according to the respective central frequencies fkOptimized chirp rate and muk' and optimized initial phase
To obtain linear frequency modulation LFM signal waveform, i.e. final sub-array LFM signal waveform sk' is:
wherein s isk' represents the optimized LFM signal waveform of the kth sub-array, fkDenotes the center frequency, μ 'of the LFM signal waveform of the k-th sub-matrix'kIndicates the chirp rate, T, of the kth subarray optimizationeIndicating the pulse width of radar transmitted signals
Indicating the initial phase of the kth subarray optimization.
The partial correlation waveform design method of the MIMO radar adopts the subarray structure, and due to the particularity of the subarray structure, independent constraint on the emission energy coverage map is not needed, so that the waveform is easy to generate, and the matching degree of the emission energy coverage map is good; in addition, the invention ensures that the pulse synthesis result of each angle in the expected direction has lower side lobe by optimizing the signal bandwidth, and the main lobe is not widened.
Example two
The beneficial effects of the present invention are further described by simulation experiments below.
1. Simulation conditions are as follows:
simulation conditions one are as follows:
the transmitting array of the MIMO radar is a uniform linear array, the number M of the transmitting array elements is equal to 20, the distance between the array elements is half wavelength, and the time width T of the signal is widee100us, total bandwidth of transmission signal B2 MHz, beam width of desired transmission energy coverage map 20 °, and beam pointing θ 00 deg.. For the invention, in order to ensure the simulation conditions to be consistent, the number M of the transmitting array elements is 20, wherein the number M of the sub-arrays14, the number M of array elements of each subarray 25, and the upper limit of the signal bandwidth Bmax＝2MHz。
And (2) simulation conditions are as follows:
the transmitting array of the MIMO radar is a uniform linear array, the number M of the transmitting array elements is equal to 20, the distance between the array elements is half wavelength, and the time width T of the signal is widee100us, total bandwidth of transmission signal B2 MHz, beam width of desired transmission energy coverage map 20 °, and beam pointing θ 020 deg. is equal to. For the invention, in order to ensure the simulation conditions to be consistent, the number M of the transmitting array elements is 20, wherein the number M of the sub-arrays14, the number M of array elements of each subarray 25, and the upper limit of the signal bandwidth Bmax＝2MHz。
2. Simulation content and result analysis
Simulation experiment 1:
under simulation conditions, the LFM signal partial correlation waveforms are designed by the method of the present invention and the prior art method respectively, and the emission energy coverage maps of the two methods are compared, please refer to fig. 2, fig. 2 is a comparison graph of the emission energy coverage maps of the waveforms designed by the prior art method and the method of the present invention under simulation conditions according to the embodiment of the present invention, wherein the abscissa in fig. 2 is an angle, the unit is degree, and the ordinate is normalized amplitude, the unit is dB.
As can be seen from fig. 2, although the method of the present invention does not impose a separate constraint on the emission energy coverage map, the matching degree with the expected emission energy coverage map is still good, and the performance is similar to that of the existing method, but because no separate constraint is imposed, the method of the present invention designs the waveform more quickly.
Simulation experiment 2:
under simulation conditions, the method of the present invention and the existing method are respectively used to design partial relevant waveforms of the LFM signal, and the results of compressing the pulse of the synthesized signal in-5 °, 0 ° and 5 ° airspaces are compared, please refer to fig. 3 to 5, fig. 3 is a comparison graph of the waveforms of the existing method and the method of the present invention under simulation conditions, which are comprehensively pulse at-5 °; FIG. 4 is a comparison graph of waveforms of the prior art method and the proposed method under simulation conditions, which are integrated at 0 degrees according to the present invention; FIG. 5 is a comparison graph of waveforms of the prior art method and the proposed method under simulation conditions, which are integrated at 5 degrees; the abscissa of fig. 3, 4 and 5 is time in us, and the ordinate is normalized amplitude in dB.
As can be seen from fig. 3, 4 and 5, in the first conventional method, although the side lobe is low, the main lobe is wide, and the range resolution of the radar system is seriously affected; the pulse comprehensive result of the second method in the prior art has good performance at minus 5 degrees and 5 degrees, the main lobe is narrow and the side lobe is low, but the performance of the second method at 0 degree is obviously reduced, the side lobe is too high, false alarm is easily caused, and the detection performance of the radar system is reduced.
Simulation experiment 3:
in the second simulation condition, the LFM signal partial correlation waveforms are designed by the method of the present invention and the conventional method respectively, and the emission energy coverage maps of the two methods are compared, please refer to fig. 6, fig. 6 is a comparison graph of the emission energy coverage maps of the waveforms designed by the conventional method and the method of the present invention under the second simulation condition according to the embodiment of the present invention, wherein the abscissa in fig. 6 is an angle, and the unit is degree, and the ordinate is normalized amplitude, and the unit is dB.
As can be seen from fig. 6, the method of the present invention can change the center orientation of the emitted energy coverage, not only pointing to the 0 ° direction, but also maintaining the matching degree with the expected emitted energy coverage in other directions, similar to the performance of the existing method.
Simulation experiment 4:
under the second simulation condition, the method of the present invention and the existing method are respectively used to design partial correlation waveforms of the LFM signal, and the two methods are compared to synthesize the signal pulse compression result in the 20 ° space domain, please refer to fig. 7, fig. 7 is a comprehensive comparison graph of the waveforms of the existing method and the method of the present invention under the second simulation condition, which is provided by the embodiment of the present invention, at 20 ° clock; where the abscissa of fig. 7 is time in us and the ordinate is normalized amplitude in dB.
As can be seen from fig. 7, the method of the present invention still has good pulse integration performance when the center of the transmitted energy coverage map is pointed at 20 °.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (10)
1. A partial correlation waveform design method of a MIMO radar based on a subarray orthogonal LFM signal is characterized by comprising the following steps:
establishing an MIMO radar model; the MIMO radar model comprises a plurality of transmitting sub-arrays;
acquiring an LFM signal waveform of each sub-array;
processing the LFM signal waveform of each subarray to obtain a pulse comprehensive result;
constructing a cost function according to the sidelobe amplitude of the pulse synthesis result;
and optimizing the LFM signal waveform of each sub-array by using the cost function to obtain the final LFM signal waveform of the sub-array.
2. The method according to claim 1, wherein the sub-array orthogonal LFM signal-based MIMO radar partial correlation waveform design method is characterized in that the expression of the sub-array LFM signal waveform is:
wherein s iskLFM signal waveform representing the kth sub-array, k being 1,2,3, …, M1，M1Representing the number of sub-arrays, fkCenter frequency, mu, of waveform of LFM signal representing kth sub-arraykIndicates the chirp rate of the LFM signal waveform of the k-th sub-array, and muk＝Bk/Te，TeRepresents the pulse width of radar emission signal, and T represents 0-TeInternal sample time, BkThe signal bandwidth of the LFM signal waveform representing the kth sub-array,
indicating the initial phase of the LFM signal waveform for the kth sub-array.
3. The method according to claim 1, wherein the processing of the LFM signal waveform of each of the sub-arrays to obtain the pulse synthesis result comprises:
obtaining LFM signal waveform matrixes of a plurality of sub-arrays according to the LFM signal waveform of each sub-array;
forming the LFM signal waveform matrix of the sub-array into a total LFM signal waveform matrix of the whole transmitting array;
and processing the total LFM signal waveform matrix to obtain a pulse comprehensive result.
4. The method according to claim 3, wherein the processing the total LFM waveform matrix to obtain the pulse synthesis result comprises:
discretely and uniformly taking P sampling angles in a range of-3 dB of an expected emission energy coverage map, and calculating a guide vector of each sampling angle;
obtaining an echo signal according to the steering vector of the sampling angle and the total LFM signal waveform matrix;
and carrying out pulse comprehensive processing on the echo signals to obtain a pulse comprehensive result.
5. The method according to claim 4, wherein the calculation formula of the steering vector of the sampling angle is:
a(θp)＝[1 exp(j2πdsinθp/λ)…exp(j(M-1)2πdsinθp/λ)]T；
wherein, a (theta)p) Representing the sampling angle thetapP is 1,2, …, P, and the sampling angle θpSatisfies theta1＜θ2＜…＜θPM represents the total number of the transmitting array elements, d represents the transmitting array element spacing, and lambda represents the wavelength of the radar transmitting signal]TRepresenting a transpose operation.
6. The method of claim 5, wherein the expression of the pulse synthesis result is:
y(θp,l)＝xcorr(sr)＝xcorr(a(θp)TS)；
wherein l represents-Te～TeThe sampling time of the inner 2L-1 point, L is 0 to TeTotal number of sampling times in xcorr (·) denotes an autocorrelation operation, sr denotes an echo signal, and sr ═ a (θ)p)TS, S represents the total LFM signal waveform matrix.
7. The method of claim 6, wherein the cost function is expressed as:
wherein, BkSignal bandwidth representation of the waveform of the LFM signal representing the kth sub-array, BminAnd BmaxRespectively represent BkThe upper limit value and the lower limit value of (c),
the initial phase of the LFM signal waveform representing the kth sub-array,
M1indicating the number of sub-arrays.
8. The method according to claim 7, wherein the optimizing the LFM signal waveform of each sub-array by using the cost function to obtain a final sub-array LFM signal waveform comprises:
respectively optimizing the signal bandwidth of the LFM signal waveform of each sub-array and the initial phase of the LFM signal waveform of each sub-array according to the cost function to obtain the optimized signal bandwidth and the optimized initial phase;
obtaining an optimized frequency modulation slope according to the optimized signal bandwidth;
and obtaining a final sub-array LFM signal waveform according to the optimized frequency modulation slope and the optimized initial phase.
9. The method according to claim 8, wherein the optimizing the bandwidth and the initial phase of the LFM signal waveform of each of the sub-arrays according to the cost function to obtain the optimized bandwidth and the optimized initial phase comprises:
will M1B isminAnd M10 s form a first column vector, and M is added1B ismaxAnd M12 pi component column vectors are second column vectors;
introducing an fminimax function, taking the cost function as a function of the fminimax function, taking a signal bandwidth of an LFM signal waveform of the sub-array and an initial phase of the LFM signal waveform of the sub-array as input variables of the fminimax function, taking the first column vector as a lower input variable limit of the fminimax function, and taking the second column vector as an upper input variable limit of the fminimax function;
and calling the fminimax function to optimize the signal bandwidth of the LFM signal waveform of each sub-array and the initial phase of the LFM signal waveform of each sub-array to obtain the optimized signal bandwidth and the optimized initial phase.
10. The method of claim 9, wherein the final sub-array LFM signal waveform is expressed as:
wherein s isk' represents the optimized LFM signal waveform of the kth sub-array, fkDenotes the center frequency, μ 'of the LFM signal waveform of the k-th sub-matrix'kIndicates the chirp rate, T, of the kth subarray optimizationeIndicating radar transmissionPulse width of horn
Indicating the initial phase of the kth subarray optimization.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010559445.9A CN111812612B (en) | 2020-06-18 | 2020-06-18 | MIMO radar partial correlation waveform design method based on subarray orthogonal LFM signals |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010559445.9A CN111812612B (en) | 2020-06-18 | 2020-06-18 | MIMO radar partial correlation waveform design method based on subarray orthogonal LFM signals |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111812612A true CN111812612A (en) | 2020-10-23 |
| CN111812612B CN111812612B (en) | 2024-06-25 |
Family
ID=72844810
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010559445.9A Active CN111812612B (en) | 2020-06-18 | 2020-06-18 | MIMO radar partial correlation waveform design method based on subarray orthogonal LFM signals |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111812612B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113567935A (en) * | 2021-07-20 | 2021-10-29 | 电子科技大学 | High-speed target detection method based on multi-sub-pulse processing |
| CN114152916A (en) * | 2021-11-15 | 2022-03-08 | 南京航空航天大学 | MIMO radar waveform orthogonal method based on pilot information |
| CN114280551A (en) * | 2021-12-24 | 2022-04-05 | 中国电子科技集团公司第十四研究所 | Ultra-wideband LFM signal amplitude equalization method based on microwave photons |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103592642A (en) * | 2013-10-22 | 2014-02-19 | 西安电子科技大学 | Method for designing MIMO radar waveforms |
| CN104459628A (en) * | 2013-09-21 | 2015-03-25 | 杨瑞娟 | Quasi-orthogonal frequency division multiplexing multicarrier linear FM radar signal design and processing method |
| CN106646420A (en) * | 2016-09-28 | 2017-05-10 | 西安电子科技大学 | Method for designing MIMO (Multiple-input multiple-output) radar transmitting direction diagram based on LFM (Linear Frequency Modulation) signals |
| WO2018094565A1 (en) * | 2016-11-22 | 2018-05-31 | 深圳大学 | Method and device for beamforming under pulse noise |
| US20190129003A1 (en) * | 2017-10-30 | 2019-05-02 | GM Global Technology Operations LLC | On-vehicle radar system |
| CN109946655A (en) * | 2019-03-18 | 2019-06-28 | 西安电子科技大学 | MIMO radar LFM signal zero setting waveform design method |
| CN110109065A (en) * | 2019-05-09 | 2019-08-09 | 西安电子科技大学 | MIMO radar part waveform correlation design method based on LFM signal |
| CN111257891A (en) * | 2020-02-08 | 2020-06-09 | 西北工业大学 | Deconvolution-based MIMO sonar range sidelobe suppression method |
-
2020
- 2020-06-18 CN CN202010559445.9A patent/CN111812612B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104459628A (en) * | 2013-09-21 | 2015-03-25 | 杨瑞娟 | Quasi-orthogonal frequency division multiplexing multicarrier linear FM radar signal design and processing method |
| CN103592642A (en) * | 2013-10-22 | 2014-02-19 | 西安电子科技大学 | Method for designing MIMO radar waveforms |
| CN106646420A (en) * | 2016-09-28 | 2017-05-10 | 西安电子科技大学 | Method for designing MIMO (Multiple-input multiple-output) radar transmitting direction diagram based on LFM (Linear Frequency Modulation) signals |
| WO2018094565A1 (en) * | 2016-11-22 | 2018-05-31 | 深圳大学 | Method and device for beamforming under pulse noise |
| US20190129003A1 (en) * | 2017-10-30 | 2019-05-02 | GM Global Technology Operations LLC | On-vehicle radar system |
| CN109946655A (en) * | 2019-03-18 | 2019-06-28 | 西安电子科技大学 | MIMO radar LFM signal zero setting waveform design method |
| CN110109065A (en) * | 2019-05-09 | 2019-08-09 | 西安电子科技大学 | MIMO radar part waveform correlation design method based on LFM signal |
| CN111257891A (en) * | 2020-02-08 | 2020-06-09 | 西北工业大学 | Deconvolution-based MIMO sonar range sidelobe suppression method |
Non-Patent Citations (1)
| Title |
|---|
| 李慧;赵永波;程增飞;: "基于线性调频时宽的MIMO雷达正交波形设计", 电子与信息学报, no. 05 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113567935A (en) * | 2021-07-20 | 2021-10-29 | 电子科技大学 | High-speed target detection method based on multi-sub-pulse processing |
| CN113567935B (en) * | 2021-07-20 | 2023-09-19 | 电子科技大学 | High-speed target detection method based on multi-sub-pulse processing |
| CN114152916A (en) * | 2021-11-15 | 2022-03-08 | 南京航空航天大学 | MIMO radar waveform orthogonal method based on pilot information |
| CN114280551A (en) * | 2021-12-24 | 2022-04-05 | 中国电子科技集团公司第十四研究所 | Ultra-wideband LFM signal amplitude equalization method based on microwave photons |
| CN114280551B (en) * | 2021-12-24 | 2024-02-27 | 中国电子科技集团公司第十四研究所 | Ultra-wideband LFM signal amplitude equalization method based on microwave photons |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111812612B (en) | 2024-06-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111812612B (en) | MIMO radar partial correlation waveform design method based on subarray orthogonal LFM signals | |
| CN109375213B (en) | Frequency diversity array signal processing method based on subarray division | |
| CN108693511B (en) | Moving target angle calculation method of time division multiplexing MIMO radar | |
| CN110927661A (en) | Single-basis expansion co-prime array MIMO radar DOA estimation method based on MUSIC algorithm | |
| CN108710112B (en) | Space-time coding array space smoothing decorrelation spectrum estimation method | |
| CN110058218B (en) | Radio frequency stealth emission beam forming method and system based on four-dimensional antenna array | |
| CN110346764B (en) | MIMO radar target distance angle decoupling method | |
| CN110412570B (en) | HRWS-SAR imaging method based on spatial pulse phase coding | |
| CN110471035B (en) | Coherent FDA radar transmitting beam synthesis method based on two-dimensional space-time coding | |
| CN114895260B (en) | Echo separation method for pitching space-time coding space-borne SAR system | |
| Wang et al. | Subarray-based frequency diverse array for target range-angle localization with monopulse processing | |
| CN114002673A (en) | Satellite-borne passive SAR non-cooperative signal sensing system and multi-dimensional parameter estimation method | |
| CN111537997B (en) | Three-dimensional radar imaging method based on MIMO and compressed sensing technology | |
| EP1629301B1 (en) | Method and system for unambiguous angle resolution of a sparse wide-band antenna array | |
| CN113917424B (en) | Ground clutter suppression method for ground MIMO radar based on DDMA and blind source separation | |
| CN113238212B (en) | Space-time coding-based frequency diversity array radar range resolution enhancement method | |
| CN110196417A (en) | The bistatic MIMO radar angle estimating method concentrated based on emitted energy | |
| CN110879017B (en) | Missile-borne detection device based on DBF | |
| CN113281732A (en) | MIMO radar target positioning method and system based on space-time coding | |
| CN113376590A (en) | Design method for time delay among array elements in space-time coding array radar | |
| CN108761433B (en) | High-resolution imaging method using MIMO sonar difference array processing | |
| Lesturgie | Improvement of high-frequency surface waves radar performances by use of multiple-input multiple-output configurations | |
| CN115436888A (en) | Method and system for inhibiting nonstationary clutter of space-based early warning radar | |
| CN112068129B (en) | Concentric ring array electromagnetic vortex radar imaging method | |
| CN113820665A (en) | Time diversity array subarray division-based airspace coverage enhancement method |
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 |