CN108508413B - Target detection method based on probability statistics under low signal-to-noise ratio condition - Google Patents
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- 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
- G01S7/28—Details of pulse systems
- G01S7/285—Receivers
- G01S7/292—Extracting wanted echo-signals
- G01S7/2923—Extracting wanted echo-signals based on data belonging to a number of consecutive radar periods
- G01S7/2927—Extracting wanted echo-signals based on data belonging to a number of consecutive radar periods by deriving and controlling a threshold value
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- 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
- G01S13/06—Systems determining position data of a target
- G01S13/42—Simultaneous measurement of distance and other co-ordinates
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- 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
- G01S13/06—Systems determining position data of a target
- G01S13/42—Simultaneous measurement of distance and other co-ordinates
- G01S13/44—Monopulse radar, i.e. simultaneous lobing
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- 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
- G01S7/28—Details of pulse systems
- G01S7/285—Receivers
- G01S7/292—Extracting wanted echo-signals
- G01S7/2923—Extracting wanted echo-signals based on data belonging to a number of consecutive radar periods
- G01S7/2926—Extracting wanted echo-signals based on data belonging to a number of consecutive radar periods by integration
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Abstract
The invention belongs to the technical field of radar signal processing, and particularly relates to a target detection method based on probability statistics under a low signal-to-noise ratio condition. The method comprises the steps of taking a single pulse in observation time as a processing object, covering an interested observation area by adopting a simultaneous multi-beam method, obtaining a target echo envelope after pulse compression of all pulse echoes in the observation area, carrying out constant false alarm detection on the echo envelope, carrying out statistics and recording on echo envelope detection frequencies of different azimuth units and distance units, and finally drawing a probability histogram to carry out detection judgment according to threshold crossing frequency distribution of the different azimuth units and distance units so as to finish a target detection process. The method provided by the invention is not only suitable for single-pulse target detection under low signal-to-noise ratio, but also can be used as an auxiliary detection means for target detection which is not ideal after multi-pulse long-time accumulation. The method provided by the invention has small data processing amount, meets the real-time processing requirement of a hardware platform, and is suitable for engineering realization.
Description
Technical Field
The invention belongs to the technical field of radar signal processing, and particularly relates to a target detection method based on probability statistics under a low signal-to-noise ratio condition.
Background
Low signal-to-noise ratio target detection is a hot issue in modern radar research. The radar is used as main electronic information equipment in modern war, always takes charge of battlefield information acquisition, processing and circuit realization tasks, and can perform positioning tracking and imaging identification on a target only by determining whether an interested target exists and acquiring related information such as target speed, angle and the like. With the electromagnetic environment in a battlefield becoming more and more complex, clutter and noise interference are serious, the application of stealth technology reduces the detectable characteristics of targets, and the low-interception technology applies extremely-wideband frequency modulation technology, noise-like modulation and inter-or directional diagram pseudo-random scanning, which causes the signal-to-noise ratio of received target signals to be very low, so that the detection of radar becomes very difficult. Some unwanted interference signals are inevitably received while the target signal is received, and background noise interference in the electromagnetic environment is inherent in radar signal processing, so in order to determine whether the target signal exists in the radar echo, the radar signal processor must have a step of judging the presence or absence of the target. The judgment capability of the early radar target detection system on the target is totally dependent on the experience of operators, and the modern radar system adopts an automatic detection system, so that the defect that the target detection performance is limited by the capability of workers is overcome. The automatic detection system applies a statistical decision theory to target detection, sets a detection threshold in advance, and then detects a target according to a decision criterion. However, if the detection threshold is set to be constant, the false alarm probability may rapidly rise when the average power of the background clutter increases by several decibels under the non-stationary clutter, so that the processing capability of the computer is saturated, and the normal operation of the radar system is affected. Therefore, a constant false alarm rate detection method is adopted in the radar target detection process, and the detection threshold is adaptively changed according to the change of the clutter intensity so as to obtain the maximum detection probability and the constant false alarm probability, but the constant false alarm rate target detection technology has requirements on the signal-to-noise ratio, and the detection result is poor under the condition of low signal-to-noise ratio. Many scholars propose long-time accumulation methods for the target detection problem under the condition of low signal-to-noise ratio, but with the development of new system radars and increasingly complex electromagnetic interference environments, the long-time accumulation target detection methods sometimes do not effectively improve the signal-to-noise ratio, so the target detection effect is not ideal.
Disclosure of Invention
The invention provides a target detection method under the condition of low signal-to-noise ratio based on probability statistics, aiming at the problem of target detection in the modern radar research. The invention is not limited to the working system of the radar generally, and is not only suitable for the low signal-to-noise ratio target detection of the single pulse, but also suitable for the low signal-to-noise ratio target detection after the multi-pulse is accumulated for a long time. The method can effectively improve the target detection accuracy under the condition of low signal-to-noise ratio, and the data volume processed by the algorithm is small, thereby being easy to realize in engineering.
The technical scheme of the invention comprises the following steps:
s1, according to the azimuth and distance range covered by power in radar work, dividing an interested observation area into an azimuth unit and a distance unit, wherein the azimuth unit theta belongs to { theta ∈ ini1,2,. and a distance element r ∈ { r }j1,2, and N respectively represent the number of azimuth units and the number of distance units of the area;
s2, according to the unit division of the interested observation area towards which the radar antenna faces in the step S1, each unit channel of the receiver antenna adopts band-pass orthogonal sampling to collect echo signals of different direction units and distance units;
s3, carrying out data preprocessing on the echo signals collected and received in the step S2, then obtaining baseband echo signals through digital down-conversion, and carrying out low-pass filtering on the baseband echo signals to eliminate interference and noise outside a bandwidth;
s4, dividing orientation units { theta ] according to the observation region of interest in the step S1 i1,2, and dividing a coverage observation area by adopting a simultaneous multi-beam method to form a beam corresponding to the ith azimuth unitFractional azimuth unit { theta }iObtaining the beam weight vector W corresponding to the ith azimuth unit by | (i ═ 1,2,) and ·, M |, and obtaining the beam weight vector W corresponding to the ith azimuth uniti＝[w0i,w1i,···,w1i,···,wLi]，wliWeighting coefficients for the ith (L belongs to (0,1, L-1)) unit channel, wherein L is the number of elements of an array antenna adopted by a receiver;
s5, multiplying the beam weight vector obtained in the step S4 and the baseband echo signal obtained in the step S3 to obtain a baseband echo signal containing azimuth information;
s6, performing pulse compression processing on the baseband echo signal containing the azimuth information in the step S5, wherein the pulse compression is realized by using a matched filtering method, and finally obtaining the baseband echo signal containing the azimuth information after the pulse compression;
s7, according to the baseband echo signals which are obtained in the step S6 and contain orientation information and are subjected to pulse compression, threshold detection is carried out on the envelopes of all echo signals in the observation time, and the distance unit and the orientation unit of each echo envelope passing through the threshold are counted and recorded;
s8, according to the distance unit and orientation unit statistical results of the echo envelope threshold in the step S7, respectively making probability histograms of detection frequencies corresponding to different orientation units and different distance units;
s9, carrying out detection judgment according to the probability histograms of different orientation units and different distance units obtained in the step S8, and comparing the detection frequency distribution in the probability histograms corresponding to the different orientation units and the different distance units, wherein the threshold detection frequency in the probability histograms is obviously higher than that of other judgment targets, and the corresponding orientation units and distance units are the orientation and distance information of the targets;
s10, if the detection judgment of the probability histogram in the step S9 can not give an accurate target detection result, adopting the following improved probability histogram detection judgment method: adjusting the window width of the probability histogram according to the size of the azimuth and distance units in the step S1, repeating the detection and judgment of the probability histogram in the step S9 until the frequency distribution of the probability histogram can obviously give a target detection result, and finally outputting the target detection result;
and for target detection under the condition of low signal-to-noise ratio by adopting long-time accumulation, carrying out long-time accumulation on the echo signals after pulse compression obtained in the step S6, obtaining the echo signals after the long-time accumulation, and repeating the steps S7-S10.
The invention has the following advantages:
(1) the method provided by the invention can improve the target detection performance of the radar to the observation area under the conditions of low signal-to-noise ratio and high false alarm probability.
(2) The method provided by the invention is suitable for single-pulse target detection.
(3) The method provided by the invention is suitable for detecting the target with low signal-to-noise ratio after long-time accumulation.
(4) The method provided by the invention can be used for multi-target detection.
(5) The method provided by the invention has small data processing amount, is suitable for real-time processing and is easy to realize in engineering.
Drawings
FIG. 1 is a flow chart of a method implementation proposed by the present invention;
FIG. 2 is a schematic diagram of observation region azimuth cell and range cell partitioning according to the proposed method of the present invention;
figure 3 is a schematic diagram of a simultaneous multi-beam method of receiving signals in an embodiment of the present invention;
FIG. 4 is a schematic illustration of constant false alarm target detection in an embodiment of the present invention;
FIG. 5 is a probability histogram of orientation unit 1 of measured data in an embodiment of the invention;
FIG. 6 is a probability histogram of the orientation unit 2 of the measured data in one embodiment of the invention;
FIG. 7 is a probability histogram after a change in distance cells in an embodiment of the invention;
FIG. 8 is a graph of the relationship between detection probability and signal-to-noise ratio for different false alarm probabilities according to the simulation of the present invention;
FIG. 9 is a graph of the relationship between detection probability and false alarm probability for different signal-to-noise ratios simulated by the present invention;
Detailed Description
The invention is further described with reference to the following drawings and specific embodiments.
The radar is a pulse system radar as an example, the signal modulation form is linear frequency modulation, the carrier frequency is 300MHz, the bandwidth is 5MHz, the receiver adopts 10 units of linear array antennas which are horizontally arranged at equal intervals, the wavelength lambda is 1m, the unit interval d is 0.5m, a servo control system is arranged on the antennas, the antennas can be controlled to face an interested observation area, the azimuth range of the observation area is-45 degrees to 45 degrees, the distance range is 130Km to 200Km, the size of the azimuth unit is 10 degrees, and the distance unit is 30 m.
Referring to the method implementation flow chart in fig. 1, the target detection method under the condition of low signal-to-noise ratio based on probability statistics mainly comprises the following steps:
s1, determining an azimuth and a distance range covered by radar power according to system parameters of the radar, controlling a radar antenna to face an interested observation area in the radar power coverage by using an antenna servo system, and dividing the area into units, wherein an azimuth unit theta belongs to { theta ∈ { theta [ ]i1,2,. and a distance element r ∈ { r }j1,2 · · N }, where M and N respectively represent the number of azimuth units and the number of distance units of the region, and fig. 2 is a schematic diagram illustrating the division of azimuth units and distance units in the observation region according to the method of the present invention;
s2, according to the unit division of the interested observation area towards which the radar antenna faces in the step S1, each unit channel of the receiver antenna adopts band-pass orthogonal sampling to collect echo signals of different direction units and distance units;
s3, carrying out data preprocessing such as amplification and filtering on the echo signal acquired in the step S2, then carrying out digital down-conversion to obtain a baseband echo signal, carrying out low-pass filtering on the baseband echo signal, and eliminating interference and noise outside a bandwidth: the baseband echo signals are transmitted to a signal processing board through optical fibers for real-time processing, and can be transmitted to a large-capacity disk array through the optical fibers for post-processing;
s4, covering the orientation units in the interested observation area divided in the step S1 by adopting a simultaneous multi-beam method to obtain beam weight vectors corresponding to all the orientation units: because the signal-to-noise ratio of the target echo is very low, in order to receive the target echo signal in the interested region more completely, a plurality of beams must be formed simultaneously by adopting a simultaneous multi-beam method in a digital beam forming technology to cover the interested observation region, and the specific implementation process of the step is as follows:
the receiving antenna is a linear array antenna with L units arranged horizontally at equal intervals, and is divided into { theta (theta) according to the azimuth position unit of the observation area of interest in the step S1 i1,2, L, M, to form the weighting coefficient w of the channel of the ith unit (L is formed (0,1, L-1)) of the beam pair corresponding to the ith azimuth unitli：
Wherein a islThe amplitude weighting coefficient of the ith element of the array antenna is the corresponding beam weight vector W of the ith azimuth elementiComprises the following steps:
s5, beam weight vectors W of different azimuth units in the step S4iAnd the baseband echo signals of different unit channels of the antenna in the step S3 are multiplied to obtain a baseband echo signal containing azimuth information: multiplying the beam weight vectors of different azimuth units by baseband echo signals of different unit channels of the antenna to obtain baseband echo signals corresponding to different azimuth units, and converting the baseband echo signals of the antenna unit channels into baseband echo signals of the azimuth units, namely the baseband echo signals containing azimuth information;
s6, performing pulse compression on the baseband echo signal containing the azimuth information obtained in the step S5, wherein the pulse compression is realized by a matched filtering technology, and the baseband echo signal containing the azimuth information is finally obtained by performing convolution multiplication on a constructed filter response function h (t) and the echo signal containing the azimuth information;
the specific implementation process of the step is as follows:
if the signal modulation form of the pulse system radar is linear frequency modulation, the expression of the radar transmission signal baseband signal s (t) is as follows:
wherein T ispFor the pulse width of the transmitted signal, B is the bandwidth of the echo signal, K ═ B/TpIs the chirp rate of the echo signal. If the pulse carrier frequency of the radar system is not a constant, the waveform of the nth transmitting signal after carrier frequency modulation
Comprises the following steps:
wherein
And tnRespectively a fast time (sampling interval within a pulse) and a slow time (sampling interval between pulses) of the transmitted signal,
tn＝nTrwherein T isrPulse repetition period for radar transmission, fnThe carrier frequency of the nth pulse. Assuming that the moving target moves at a constant speed in a direction deviating from the radar direction, the initial distance at the moment when t is 0 is r0Velocity v0Then the target distance r (t) is in a time-varying relation:
r(t)＝r(tn)＝r0+v0tn
echo time delay tau of a targetnComprises the following steps:
then receive over a period of timeTo the nth item mark echo
Can be expressed as:
wherein A isrIs the complex amplitude of echo signal, and the baseband echo containing azimuth information after coherent demodulation
Comprises the following steps:
pulse compression is accomplished by matched filtering, with the filter response h (t) being the inverse conjugate of the baseband signal of the transmitted signal.
The filter response function h (t) is compared with the baseband echo signal containing the azimuth information
Convolution multiplication is carried out, and finally, a pulse-compressed baseband echo signal containing azimuth information is obtained
"+" indicates convolution multiplication.
S7, according to the echo signals which are obtained in the step S6 and contain orientation information and are subjected to pulse compression, threshold detection is carried out on the envelopes of all the echo signals in the observation time, and a distance unit and an orientation unit of each echo envelope passing through a threshold are counted and recorded: the threshold detection in this step adopts a unit average constant false alarm rate detection method, the direction unit and the distance unit of each pulse echo enveloping the threshold are counted and recorded in the threshold detection process, and fig. 4 is an exemplary diagram of the simulation unit average constant false alarm rate target detection process of the invention;
s8, according to the statistical results of the azimuth units and the distance units of the echo envelope threshold in the step S7, respectively making probability histograms of the detection frequencies corresponding to different azimuth units and different distance units: the probability histogram provides a global description of a target detection result, and the frequency of the same unit can be regarded as the detection probability of the target, so that in this embodiment, the horizontal axis in the planar rectangular coordinate system is used as a distance unit, and the vertical axis is used as the frequency of the threshold, and probability histograms corresponding to different azimuth units are respectively drawn, and fig. 5 and 6 give probability histograms of an azimuth unit 1 and an azimuth unit 2 in the measured data;
s9, carrying out detection judgment according to the probability histograms of different orientation units and different distance units obtained in the step S8, wherein the threshold passing detection frequency in the probability histograms is obviously higher than that of other judgment targets, and the corresponding orientation units and distance units are the information of the orientation and distance of the targets: in order to improve the target detection probability, the false alarm probability is usually set to be very high, so that the detection threshold is low, the target is possibly interfered by clutter and noise to cause inaccurate detection in single detection, at the moment, the azimuth unit and the distance unit of which all echoes envelope the threshold in the observation time are counted, the frequency of the detection of the same azimuth unit and the distance unit is obviously higher than that of other judgment targets, and therefore the target can be detected and judged by using the frequency distribution of the probability histogram;
s10, if the detection judgment of the probability histogram in the step S9 can not give an accurate target detection result, adopting the following improved probability histogram detection judgment method: adjusting the window width of the probability histogram according to the size of the azimuth and distance units in the step S1, repeating the detection and judgment of the probability histogram in the step S9 until the frequency distribution of the probability histogram can obviously give a target detection result, and finally outputting the target detection result:
according to the stepsThe echo after pulse compression in step S6 has an echo envelope center τnDetermines the distance unit of the target, but the center tau of the echo envelopenIs a variable that may cause echoes to spread with range bin energy as the target moves across the range bin, causing a decrease in signal-to-noise ratio. When the observation area is covered by adopting a simultaneous multi-beam method, when the interval of division of the azimuth units is small, the target movement easily crosses the azimuth units, so that the energy diffusion of the echo in the same azimuth unit is caused, and the signal-to-noise ratio is reduced. Therefore, the target motion may cause the energy of the target echo to spread to other range cells and azimuth cells, resulting in a decrease in the signal-to-noise ratio of the target echo. The invention adopts a probability histogram improved detection judgment method, which can adjust the window width of the probability histogram according to the size of the azimuth and distance unit in the step S1 and improve the target detection performance. Fig. 7 shows a histogram of the probability after adding distance cells compared to fig. 6.
For the low signal-to-noise ratio target detection adopting long-time accumulation, the echo signal obtained after the pulse compression in the step S6 is accumulated for a long time to obtain an echo signal after the long-time accumulation, and the steps S7-S10 are repeated;
the specific implementation process of the step is as follows:
the long-time accumulation method is implemented by accumulating the n pulse-compressed echoes obtained in step S6. The long-time accumulation method is classified into coherent accumulation and non-coherent accumulation according to whether phase information of an echo is utilized or not. For coherent accumulation, the echo envelope after long-time accumulation
Comprises the following steps:
therefore, echo signals are added in phase in the coherent accumulation process, the amplitude of the echo is increased to N times of the original amplitude, and the signal energy accumulation is increased to N times of the original energy accumulation2The noise phase changes randomly in the accumulation time, and the noise power is increased by N times, so the signal-to-noise ratio after coherent accumulationThe improvement is N times of the original improvement.
For non-coherent accumulation, echo envelope after long-time accumulation
Comprises the following steps:
since the phase information of the echo is discarded, the accumulation efficiency of non-coherent accumulation relative to coherent accumulation is much lower, and it is worth noting when the carrier frequency f of the echo signalnWhen the phase relation between pulses is destroyed during the change, the long-time accumulation of the target echo is usually completed by a non-coherent accumulation method, and in addition, the target span may move away from the unit during the long-time accumulation, so that the target detection performance is influenced.
From the relationship graphs (fig. 8, fig. 9) of the simulated target detection probability, the signal-to-noise ratio and the false alarm probability, it can be seen that in the target detection under the condition of low signal-to-noise ratio, the detection probability increases with the increase of the false alarm probability, but when the false alarm probability increases, the detection threshold becomes lower, and the detection result of the target is easy to be misjudged, so that the detection accuracy of the target is reduced. The signal-to-noise ratio accumulated in some application scenes by adopting a long-time accumulation method may still not meet the requirement of target detection, and particularly, the phase relationship between the received pulse echoes is difficult to determine, and the signal-to-noise ratio is not obviously improved after the long-time accumulation. Therefore, the low signal-to-noise ratio target detection method based on probability statistics, which is provided by the invention, uses a single pulse in observation time as a processing object, adopts a simultaneous multi-beam method to cover an interested observation area, obtains a target echo envelope by pulse compression of all pulse echoes in the observation area, then performs constant false alarm detection on the echo envelope, performs statistical recording on the detection frequency of the echo envelopes of different azimuth units and distance units, and finally draws a probability histogram to perform detection judgment according to the threshold-crossing frequency distribution of the different azimuth units and distance units, thereby completing the target detection process. The method provided by the invention is not only suitable for single-pulse target detection under low signal-to-noise ratio, but also can be used as an auxiliary detection means for target detection which is not ideal after multi-pulse long-time accumulation. The method provided by the invention has small data processing amount, meets the real-time processing requirement of a hardware platform, and is suitable for engineering realization.
Claims (6)
1. A target detection method under the condition of low signal-to-noise ratio based on probability statistics is characterized by comprising the following steps:
s1, according to the azimuth and distance range covered by power in radar work, dividing an interested observation area into an azimuth unit and a distance unit, wherein the azimuth unit theta belongs to { theta ∈ iniI 1,2, …, M and a distance element r e { r ∈ { r [ ]j1,2, …, N, M and N respectively represent the number of azimuth elements and the number of distance elements of the area;
s2, according to the unit division in the observation area in the step S1, acquiring and receiving echo signals in different units by a receiver antenna;
s3, carrying out data preprocessing on the echo signals collected and received in the step S2, then obtaining baseband echo signals through digital down-conversion, and carrying out low-pass filtering on the baseband echo signals to eliminate interference and noise outside a bandwidth;
s4, dividing orientation units { theta ] according to the observation region of interest in the step S1i1,2, …, M, and covers azimuth cells { θ } divided in the observation area by a simultaneous multi-beam method to form a beam corresponding to the i-th azimuth celliI |, 1,2, …, M }, and a beam weight vector W corresponding to the i-th azimuth cell is obtainedi＝[w0i,w1i,…,w1i,…,wLi]，wliWeighting coefficients for the ith (L belongs to (0,1, … L-1)) element channel, wherein L is the number of elements of an array antenna adopted by a receiver;
s5, multiplying the beam weight vector obtained in the step S4 and the baseband echo signal obtained in the step S3 to obtain an echo signal containing azimuth information;
s6, performing pulse compression processing on the echo signal containing the azimuth information in the step S5, wherein the pulse compression is realized by using a matched filtering method, and finally obtaining the echo signal containing the azimuth information after the pulse compression;
s7, according to the echo signals which are obtained in the step S6 and contain orientation information and are subjected to pulse compression, threshold detection is carried out on the envelopes of all the echo signals in the observation time, and the distance units and the orientation units of each echo envelope passing through the threshold are counted and recorded;
s8, according to the distance unit and orientation unit statistical results of the echo envelope threshold in the step S7, respectively making probability histograms of detection frequencies corresponding to different orientation units and different distance units;
s9, carrying out detection judgment according to the probability histograms of different orientation units and different distance units obtained in the step S8, and comparing the detection frequency distribution in the probability histograms corresponding to the different orientation units and the different distance units, wherein the threshold detection frequency in the probability histograms is obviously higher than that of other judgment targets, and the corresponding orientation units and distance units are the orientation and distance information of the targets;
s10, if the detection judgment of the probability histogram in the step S9 can not give an accurate target detection result, adopting the following improved probability histogram detection judgment method: and (4) adjusting the window width of the probability histogram according to the size of the azimuth and distance units in the step (S1), repeating the detection and judgment of the probability histogram in the step (S9) until the frequency distribution of the probability histogram can obviously provide a target detection result, and finally outputting the target detection result.
2. The method for detecting the target under the condition of low signal-to-noise ratio based on the probability statistics as claimed in claim 1, wherein: the procedure of the pulse compression processing in step S6 is as follows:
if the signal modulation form of the pulse system radar is linear frequency modulation, the expression of the radar transmission signal baseband signal s (t) is as follows:
wherein T ispFor the pulse width of the transmitted signal, B is the bandwidth of the echo signal, K ═ B/TpIs the chirp rate of the echo signal; if the pulse carrier frequency of the radar system is notIs constant, the waveform of the n-th transmitting signal after carrier frequency modulation
Comprises the following steps:
wherein
And tnRespectively the fast time and the slow time of the transmitted signal,
tn＝nTrwherein T isrPulse repetition period for radar transmission, fnThe carrier frequency of the nth pulse; assuming that the moving target moves at a constant speed in a direction deviating from the radar direction, the initial distance at the moment when t is 0 is r0Velocity v0Then the target distance r (t) is in a time-varying relation:
r(t)＝r(tn)＝r0+v0tn
echo time delay tau of a targetnComprises the following steps:
then the nth entry received within a period of time marks the echo
Can be expressed as:
wherein A isrIs the complex amplitude of echo signal, and the baseband echo containing azimuth information after coherent demodulation
Comprises the following steps:
pulse compression is accomplished by matched filtering, with the filter response h (t) being the inverse conjugate of the baseband signal:
the filter response function h (t) is compared with the echo signal containing the azimuth information
Convolution multiplication is carried out, and finally, a pulse-compressed baseband echo signal containing azimuth information is obtained
"+" indicates convolution multiplication.
3. The method for detecting the target under the condition of low signal-to-noise ratio based on the probability statistics as claimed in claim 1, wherein: the threshold detection in step S7 adopts a unit average constant false alarm rate detection method.
4. The method for detecting the target under the condition of low signal-to-noise ratio based on the probability statistics as claimed in any one of claims 1 to 3, wherein: and for target detection under the condition of low signal-to-noise ratio by adopting long-time accumulation, carrying out long-time accumulation on the echo signals after pulse compression obtained in the step S6, obtaining the echo signals after the long-time accumulation, and repeating the steps S7-S10.
5. The method for detecting the target under the condition of low signal-to-noise ratio based on the probability statistics as claimed in claim 4, wherein: the long-time accumulation method is implemented by accumulating the n pulse-compressed echoes obtained in step S6.
6. The method for detecting the target under the condition of low signal-to-noise ratio based on the probability statistics as claimed in claim 4, wherein: the long-time accumulation method is divided into coherent accumulation and non-coherent accumulation.
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