CN117834360A - Low sidelobe pulse compression processing method based on step frequency MSK signal - Google Patents
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- H—ELECTRICITY
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/10—Frequency-modulated carrier systems, i.e. using frequency-shift keying
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- 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
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Abstract
The invention relates to a low sidelobe pulse compression processing method based on a step frequency MSK signal, which comprises the following steps: generating a step frequency radar waveform and an MSK communication frequency shift keying joint coding waveform to form a radar communication common signal; performing analog-to-digital conversion on a common waveform sequence of the radar communication common signal, and performing pulse compression processing on the common waveform sequence and a corresponding matching sequence to obtain a matched filtering output sequence; establishing a combined optimization mathematical model taking waveform pulse compression integral side lobe and front and rear pulse pressure peak loss of a side lobe suppressor as cost functions; solving a filter coefficient of a sidelobe canceller by using the matched filter output sequence based on the joint optimization mathematical model; and filtering the matched filtering output sequence by using the filtering coefficient of the sidelobe suppressor to obtain pulse pressure output after sidelobe suppression. The method has better radar detection performance, can improve the suppression effect on side lobes, improves the radar communication integrated pulse compression performance, and has small operand.
Description
Technical Field
The invention belongs to the technical field of radar communication integrated waveform signal processing, relates to design of a radar communication common waveform and research of a side lobe suppression method, and particularly relates to a low side lobe pulse compression processing method based on a step frequency MSK signal.
Background
The radar communication integrated system can complete the functions of radar detection and communication information transmission at the same time, and aims to break the isolation between the radar and communication systems, so that the radar and communication systems can cooperate with each other, and the resource utilization rate of the system is improved. The design of the transmitting waveform is mainly divided into a waveform multiplexing system, a waveform cooperation system and a waveform sharing system, wherein the waveform sharing system adopts the same transmitting waveform to complete two functions of communication and radar.
The pulse compression technology is a technology capable of improving the acting distance and the distance resolution of the radar at the same time, and a receiving end converts a large-bandwidth signal into a narrow pulse through pulse compression processing so as to achieve higher distance resolution. The pulse compression technology solves the contradiction between the distance resolution capability and the acting distance of the radar, and is widely applied to modern radars, but after pulse pressure is filtered by matching, a series of distance side lobes with the amplitude lower than that of the main lobe inevitably appear at the two sides of the main lobe. The side lobe is the least favorable but unavoidable problem in the pulse compression processing, and is harmful, if the side lobe of a large target is higher, the side lobe can be mistakenly regarded as a main lobe in the signal processing, so that false target misjudgment is caused; and side lobes of a large target can suppress or mask main lobes of adjacent smaller targets, resulting in the small target being submerged, thereby causing missed judgment of the target. The low sidelobe performance of radar waveforms is one of the keys of pulse compression radar systems, which can avoid masking of weak targets by strong target sidelobes, thereby improving the detection capability of the radar.
In radar communication integrated systems, different pulses are required to transmit different signal waveforms in order to carry communication information. The difference between the pulses can cause the side lobe to lose regularity after matched filtering, and the problem of larger side lobe exists.
The basic idea of the design scheme of the conventional radar communication common waveform is to embed communication modulation information in a common radar waveform, and an integrated waveform based on constant envelope phase modulation, an LFM-MSK modulation mode and the like are provided. The existing sidelobe suppression correlation method mainly comprises two methods, wherein the first method is to suppress side lobes in a weighted windowing mode, and the second method is to suppress sidelobe levels by designing a minimum integral sidelobe (Integrated Sidelobe Level, ISL) filter under the condition of a given radar waveform, specifically, the integral sidelobe levels are taken as an objective function, and the coefficient of the minimum ISL is solved by adopting a least square iterative algorithm.
However, the characteristic that the blurring function of the linear frequency modulation waveform (Linear Frequency Modulation, LFM) -minimum shift keying (Minimum Shift Keying, MSK) signal is not concentrated in the existing radar communication common waveform is not beneficial to the resolution of the target; moreover, the existing method for suppressing side lobes by weighting windowing has no obvious suppression effect on the side lobes, and can cause the widening of main lobes; in addition, the serious loss of signal to noise ratio can be caused while the side lobe is greatly reduced by designing the non-matched filter, and meanwhile, the calculation amount is large and the calculation is complex by solving the filter coefficient by the least square iteration method.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a low sidelobe pulse compression processing method based on a step frequency MSK signal. The technical problems to be solved by the invention are realized by the following technical scheme:
the embodiment of the invention provides a low sidelobe pulse compression processing method based on a step frequency MSK signal, which comprises the following steps:
step 1, generating a joint coding waveform of a step frequency radar waveform and MSK communication frequency shift keying to form a radar communication common signal;
step 2, carrying out analog-to-digital conversion on the common waveform sequence of the radar communication common signal, and carrying out pulse compression processing on the common waveform sequence and the corresponding matching sequence to obtain a matched filtering output sequence;
step 3, establishing a combined optimization mathematical model taking waveform pulse compression integral sidelobes and front and rear pulse pressure peak loss of a sidelobe suppressor as cost functions;
step 4, solving a filter coefficient of a sidelobe canceller by using the matched filter output sequence based on the joint optimization mathematical model;
and step 5, filtering the matched filtering output sequence by utilizing the filtering coefficient of the sidelobe suppressor to obtain pulse pressure output after sidelobe suppression.
Compared with the prior art, the invention has the beneficial effects that:
in the low sidelobe pulse compression processing method, the radar communication common signal is a joint coding waveform of a step frequency radar waveform and MSK communication frequency shift keying, the fuzzy function of the waveform has obvious peak in an infinitely small range at the origin, and the radar communication common signal has more concentrated fuzzy function characteristics than the conventional LFM-MSK signal and has better radar detection performance; when the common waveform sequence is processed, the signal is firstly subjected to pulse compression processing to improve the signal to noise ratio, and then is subjected to filtering by matching with the filtering output sequence to further inhibit side lobes, so that the inhibiting effect on the side lobes can be improved, and the main lobes are prevented from widening; because the combined optimization mathematical model taking waveform pulse compression integral side lobe and peak loss of pulse pressure before and after a side lobe suppressor as cost functions is established, the pulse pressure side lobe can be effectively suppressed under the condition of smaller peak loss, the radar communication integrated pulse compression performance is improved, and meanwhile, compared with the traditional least square iteration method, the method is faster in speed, small in operation amount and simple in calculation.
Drawings
Fig. 1 is a flow chart of a low sidelobe pulse compression processing method based on a step frequency MSK signal according to an embodiment of the present invention;
FIG. 2 is a time domain waveform diagram of a radar communication common signal transmit burst;
FIG. 3 is a time-frequency relationship diagram of a step-frequency MSK joint encoded signal;
FIG. 4 is an enlarged view of a time domain waveform diagram of a common waveform sub-pulse;
FIG. 5 is a three-dimensional plot of the blur function of a step-frequency MSK signal;
FIG. 6 is a pulse compression contrast diagram;
fig. 7 is a window result diagram of a low sidelobe pulse compression processing method based on a step frequency MSK signal.
Detailed Description
The present invention will be described in further detail with reference to specific examples, but embodiments of the present invention are not limited thereto.
Example 1
Referring to fig. 1, fig. 1 is a flow chart of a low sidelobe pulse compression processing method based on a step frequency MSK signal according to an embodiment of the present invention.
The low side lobe pulse compression processing method based on the step frequency MSK signal is mainly used for the integrated waveform design of radar communication and the pulse compression signal processing of restraining side lobes, can be used for a transmission system of a networked radar, and improves the detection capability of the radar, and specifically comprises the following steps:
and step 1, generating a joint coding waveform of the step frequency radar waveform and the MSK communication frequency shift keying to form a radar communication common signal. The method specifically comprises the following steps:
step 1-1, generating N pulse equal interval step frequency radar signals.
Specifically, the equidistant step frequency signal is characterized in that the frequency interval between adjacent pulses is fixed, and then the step frequency radar signal with fixed frequency difference is:
wherein T is time, N is the number of sub-pulses in a transmission pulse, T s The time width of the sub-pulses, Δf, is the frequency difference.
Step 1-2, generating an MSK modulated communication signal.
Specifically, the minimum Frequency shift keying (MSK) is a special form of Frequency Shift Keying (FSK), the MSK obtains a quadrature signal with a minimum modulation index of 0.5, and the communication signal modulated by the MSK is generated by using I/Q quadrature modulation:
wherein M is the number of code elements, T b For symbol duration wide, I m The input data is processed into bipolar code elements and then subjected to differential coding and serial-parallel conversion to obtain odd-number data, Q m An even-number path data after differential coding and serial-parallel conversion is carried out after the input data is processed into a bipolar code element, f c Is the carrier frequency of the signal.
And step 1-3, modulating the carrier frequency in the MSK modulated communication signal by using the step frequency of the step frequency radar signal to form a radar communication common signal.
Specifically, the expression of the radar communication common signal is:
and step 2, carrying out analog-to-digital conversion on the common waveform sequence of the radar communication common signal, and carrying out pulse compression processing on the common waveform sequence and the corresponding matching sequence to obtain a matched filtering output sequence. The method specifically comprises the following steps:
step 2-1, to satisfy the Nyquist sampling theorem of sampling frequency f s Analog-to-digital conversion is carried out on the common waveform sequence more than or equal to 2MΔf, namely the common waveform sequence is sampled, and a discrete sequence is obtained:
s＝[s 1 ,s 2 ,...,s L ] T ；
wherein l=mt b f s For the number of sampling points, M is the number of code elements, T b For symbol duration wide, Δf is the frequency difference.
And 2-2, constructing impulse response of the time domain matched filter by adopting a time domain convolution method.
Specifically, a time domain convolution method is adopted, and according to h match (t)＝s * (-t) constructing an impulse response of the time domain matched filter, wherein the impulse response is obtained by performing time deconvolution and conjugation on a transmitting signal, and performing linear convolution on the impulse response and the transmitting signal, namely:
s o (t)＝s(t)*s * (-t)；
where s (t) is a discrete sequence at time t.
Step 2-3, carrying out matched filtering on the common waveform sequence by using the matched sequence to obtain a matched filtering output sequence which is:
s o ＝s*h match ＝[s o1 ,s o2 ,...,s oL ,...s o2L ,s o2L-1 ] T 。
and step 3, establishing a combined optimization mathematical model taking waveform pulse compression integral side lobes and front and rear pulse pressure peak loss of a side lobe suppressor as cost functions.
Specifically, assume that the input sequence of the sidelobe canceller is x= [ x 1 ,x 2 ,...,x n ] T The weighting coefficient (filter coefficient) is h= [ h ] 1 ,h 2 ,...,h n ] T Where n represents the length of the input signal and the filter, n=2l—1, the output after pulse compression is r (k) =x (k) ×h (k). Let the convolution matrix X of the sidelobe canceller input signal be:
the output signal of the sidelobe canceller is r=xh and the output peak value is x H h。
Integrating the output signal of the sidelobe canceller to obtain a waveform pulse compression integration sidelobe:
ISL＝(Xh) H G(Xh)＝h H X H GXh
in the above formula, G is a 2n-1 dimensional square matrix, diagonal elements except the nth element are all 1, and the rest elements are all 0, namely:
defining the performance penalty of a sidelobe canceller as the penalty of the peaks before and after weighting, i.e. the difference between the peak amplitudes before and after output, can be expressed as Lost = σ - |x H h is the amplitude of the peak value of the input signal of the sidelobe canceller, namely the peak amplitude of the output signal after matched filtering; sigma is a known constant for determining the common waveform input signal.
Further, the establishment of a combined optimization mathematical model taking the minimized waveform pulse compression integral side lobe and the front and back peak loss of a side lobe suppressor as objective functions is as follows:
min.h H X H GXh+λ(σ-x H h) 2
wherein, lambda (0 is less than or equal to lambda is less than or equal to 1) is a weight factor, and lambda represents the specific gravity distribution of the performance loss and the integral sidelobes in the joint design.
And 4, solving the filter coefficient of the sidelobe canceller by using the matched filter output sequence based on the joint optimization mathematical model.
Specifically, since the input signal of the sidelobe canceller is the output signal after the matched pulse compression, the x-sequence is determined, and hence the expression of the joint optimization mathematical model is a second order function with respect to the variable h (unconstrained optimization problem with respect to the filter coefficient), and h i The previous coefficient being the input signalTherefore, the combined optimization mathematical model is a concave function, and a minimum exists, and the weighted coefficient (namely the weighted coefficient) of the sidelobe canceller can be obtained by deriving the combined optimization mathematical model. The process for deriving the combined optimization mathematical model comprises the following steps:
the filter coefficients of the sidelobe canceller were found to be:
h＝λσ(X H GX+λxx H ) -1 (x H ) T 。
and step 5, filtering the matched filtering output sequence by utilizing the filtering coefficient of the sidelobe canceller to obtain pulse pressure output after sidelobe suppression.
Specifically, the pulse pressure output after sidelobe suppression can be obtained by substituting the filter coefficient of the sidelobe canceller obtained in step 4 into the equation r=xh.
In the low sidelobe pulse compression processing method of the embodiment, the radar communication common signal is a joint coding waveform of a step frequency radar waveform and MSK communication frequency shift keying, a fuzzy function of the waveform has obvious peaks in an infinitely small range at an origin, and the radar communication common signal has more concentrated fuzzy function characteristics than the conventional LFM-MSK signal and has better radar detection performance; when the common waveform sequence is processed, the signal is firstly subjected to pulse compression processing to improve the signal to noise ratio, and then is subjected to filtering by matching with the filtering output sequence to further inhibit side lobes, so that the inhibiting effect on the side lobes can be improved, and the main lobes are prevented from widening; because the combined optimization mathematical model taking waveform pulse compression integral side lobe and peak loss of pulse pressure before and after a side lobe suppressor as cost functions is established, the pulse pressure side lobe can be effectively suppressed under the condition of smaller peak loss, the radar communication integrated pulse compression performance is improved, and meanwhile, compared with the traditional least square iteration method, the method is faster in speed, small in operation amount and simple in calculation. The sidelobe suppression object is more generalized, and is expanded from a common radar waveform to a radar communication integrated waveform.
Example two
Based on the first embodiment, the effect of the low sidelobe pulse compression processing method based on the step frequency MSK signal is further described through the following simulation experiment.
1. Simulation conditions:
the simulation of this embodiment sets the number of pulses and the number of symbols to m=n=20, and the time width and the symbol length of each pulse to T s ＝T b =1μs, step frequency difference Δf=1 MHz, sampling frequency f s Signal-to-noise ratio snr=10 for gaussian white noise=100 MHzdB, the number of transmitted pulses is 64, the window function uses hamming window, and the weight factor λ=1.
2. The simulation content:
in this example, 2 simulation experiments were performed using the method of example one in a gaussian white noise environment.
The simulation experiment 1 is a simulation of the common waveform step frequency MSK signal by using the method of the embodiment, and a time-frequency relation diagram, a time-domain waveform diagram, a transmitting pulse string waveform diagram and a fuzzy function three-dimensional diagram of the waveform are obtained, and the results are shown in fig. 2, 3, 4 and 5.
Fig. 2 is a time domain waveform diagram of a radar communication common signal transmission pulse train, with time on the abscissa, μs and amplitude on the ordinate.
Fig. 3 is a time-frequency relationship diagram of a step-frequency MSK joint encoded signal, the abscissa is time, the ordinate is frequency, the unit is MHz, the black line represents the frequency of a conventional step-frequency radar waveform, and the red line represents the frequency of a common waveform signal. As can be seen from fig. 3, the frequency difference between the N pulses is no longer fixed, due to the modulation of the communication information in the radar waveform, which directly causes the common waveform frequency to fluctuate on the basis of the frequency of the conventional step-frequency radar waveform.
Fig. 4 is an enlarged view of a time domain waveform of a common waveform sub-pulse, with time on the abscissa and amplitude on the ordinate, in mus. As can be seen from fig. 4, the signal is a phase continuous, constant-envelope frequency-coded waveform.
Fig. 5 is a three-dimensional plot of the blurring function of a step-frequency MSK signal, which can be seen as the doppler shift f at time delay τ=0 d There is a sharp spike at =0 and the blurring function is more concentrated than the LFM-MSK signal, which indicates that the signal has better radar detection performance.
The simulation experiment 2 is a simulation of the common waveform pulse compression by using the method of the embodiment, and a decibel value change trend chart of the signal amplitude after the pulse compression is normalized is obtained, and the result is shown in fig. 6 and 7.
Fig. 6 is a pulse compression contrast diagram, the abscissa is the number of sampling points, and the ordinate is the decibel value of the normalized signal amplitude after pulse pressure, and the unit is dB. Fig. 6 is a graph comparing pulse pressure results before and after an embodiment method, wherein a blue curve represents the results of pulse compression of a common waveform signal by matched filtering, and a red curve represents the results of pulse compression of a common waveform by the method of the present invention. It can be seen that the method of the embodiment reduces the side lobe of the radar communication common waveform from-17.1 dB to-42.7 dB, improves the main and side lobe ratio by 25.6dB, and effectively suppresses the side lobe.
Fig. 7 is a window result diagram of a low sidelobe pulse compression processing method based on a step frequency MSK signal, wherein the abscissa is the number of sampling points, and the ordinate is the decibel value of the pulse-pressure-based signal after amplitude normalization, and the unit is dB. It can be seen that, in the method of the embodiment, after the traditional weighting windowing is combined, the maximum peak side lobe of the signal is-37.8 dB, and the side lobe is increased, so that the traditional weighting windowing side lobe reducing mode is not suitable for the radar communication joint coding signal, the side lobe suppression effect cannot be achieved, and the side lobe is increased.
Table 1 shows the pulse compression comparison results of different methods.
Table 1 results of pulse compression comparisons for different methods
| Algorithm | Maximum sidelobe/dB | Pulse pressure post peak/dB |
| Matched filtering | -17.1 | 64.5916 |
| Minimum ISL filtering | -34.2 | 26.0677 |
| Block optimization mismatch filtering algorithm | -36.6 | 65.9276 |
| The method of the invention | -42.7 | 63.6586 |
As can be seen from comparison of Table 1, the method of the embodiment can further effectively reduce the pulse pressure side lobe of the radar communication common waveform under the condition of smaller peak loss.
As is clear from the comparison, in the side lobe suppression for radar communication integration, the step frequency MSK signal low side lobe processing method provided in the first embodiment can effectively suppress the side lobe of the radar communication joint coding signal, and improve the main-side lobe ratio. Thus, through the above simulation, the feasibility of the present invention was verified.
The foregoing is a further detailed description of the invention in connection with the preferred embodiments, and it is not intended that the invention be limited to the specific embodiments described. It will be apparent to those skilled in the art that several simple deductions or substitutions may be made without departing from the spirit of the invention, and these should be considered to be within the scope of the invention.
Claims (7)
1. A low side lobe pulse compression processing method based on a step frequency MSK signal is characterized by comprising the following steps:
step 1, generating a joint coding waveform of a step frequency radar waveform and MSK communication frequency shift keying to form a radar communication common signal;
step 2, carrying out analog-to-digital conversion on the common waveform sequence of the radar communication common signal, and carrying out pulse compression processing on the common waveform sequence and the corresponding matching sequence to obtain a matched filtering output sequence;
step 3, establishing a combined optimization mathematical model taking waveform pulse compression integral sidelobes and front and rear pulse pressure peak loss of a sidelobe suppressor as cost functions;
step 4, solving a filter coefficient of a sidelobe canceller by using the matched filter output sequence based on the joint optimization mathematical model;
and step 5, filtering the matched filtering output sequence by utilizing the filtering coefficient of the sidelobe suppressor to obtain pulse pressure output after sidelobe suppression.
2. The method for processing low sidelobe pulse compression based on the step frequency MSK signal according to claim 1, wherein said step 1 comprises:
step 1-1, generating a plurality of pulse equidistant stepping frequency radar signals;
step 1-2, generating MSK modulated communication signals;
and step 1-3, modulating the carrier frequency in the MSK modulated communication signal by using the step frequency of the step frequency radar signal to form a radar communication common signal.
3. The method for processing low sidelobe pulse compression based on the step frequency MSK signal according to claim 2, wherein the step frequency radar signal is:
wherein T is time, N is the number of sub-pulses in a transmission pulse, T s The time width of the sub-pulse, Δf is the frequency difference;
the MSK modulated communication signal is:
wherein M is the number of code elements, T b For symbol duration wide, I m The input data is processed into bipolar code elements and then subjected to differential coding and serial-parallel conversion to obtain odd-number data, Q m An even-number path data after differential coding and serial-parallel conversion is carried out after the input data is processed into a bipolar code element, f c Is the carrier frequency of the signal;
the radar communication common signal is:
4. the method for processing low sidelobe pulse compression based on the step frequency MSK signal according to claim 1, wherein said step 3 comprises:
defining an input signal of a sidelobe canceller as x= [ x ] 1 ,x 2 ,...,x n ] T The filter coefficient of the sidelobe canceller is h= [ h ] 1 ,h 2 ,...,h n ] T Where n represents the length of the input signal and the filter, n=2l—1, let the convolution matrix of the input signal be:
the output signal of the sidelobe canceller is r=xh and the output peak value is x H h；
Integrating the output signal to obtain the waveform pulse compression integration sidelobe:
ISL＝(Xh) H G(Xh)＝h H X H GXh；
wherein G is a 2n-1 dimensional matrix,
defining peak losses of pulse pressures before and after a sidelobe canceller as:
Lost＝σ-|x H h|
wherein σ is the amplitude of the peak of the sidelobe canceller input signal;
establishing the combined optimization mathematical model according to the output signal of the sidelobe canceller and the peak loss of pulse pressure before and after the sidelobe canceller:
min.h H X H GXh+λ(σ-x H h) 2 ；
wherein lambda (0 is less than or equal to lambda is less than or equal to 1) is a weight factor.
5. The method of step-frequency MSK signal-based low side lobe pulse compression processing according to claim 1, wherein the step 4 includes:
and deriving the combined optimization mathematical model based on the unconstrained optimization problem about the filter coefficient and the concave function with the minimum value to obtain the filter coefficient of the sidelobe canceller.
6. The method for compressing low sidelobe pulses based on step frequency MSK signals as claimed in claim 5, wherein said deriving said joint optimization mathematical model comprises:
the filter coefficients of the sidelobe canceller are:
h＝λσ(X H GX+λxx H ) -1 (x H ) T 。
7. the method for compressing pulse with low side lobe based on step frequency MSK signal according to claim 1, wherein the pulse pressure output after side lobe suppression is:
r＝Xh；
wherein X is a convolution matrix of an input signal of the sidelobe canceller, and h is a filter coefficient of the sidelobe canceller.
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