Radar signal pulse sequence extraction method based on cross-correlation and estimation signal-to-noise ratio

Abstract

The invention discloses a radar signal pulse sequence extraction method based on cross-correlation and an estimated signal-to-noise ratio, and belongs to the field of radar signal processing. The method comprises the following steps: framing a sampling signal, calculating a product sequence of short-time energy and a zero-crossing rate of each frame, constructing a rectangular wave according to a single pulse length and a frame shift, segmenting a signal sequence according to a cross-correlation result of the rectangular wave and the product sequence, each segment comprising an effective pulse and noise before and after the pulse; then, effective pulses in each segment are accurately extracted, a segment of noise is taken in front of the segment, the estimated signal-to-noise ratio of the pulses is calculated, noise normalization processing is conducted on the whole sequence, and finally the starting point and the end point of the pulses are detected according to the value of the estimated signal-to-noise ratio. The method does not depend on threshold setting, extraction errors caused by improper threshold setting are avoided, the method is small in calculation amount and high in practicability, and radar pulses in multiple scenes can be rapidly and accurately extracted.

Description

Technical Field

[0001] The present invention relates to the technical field of radar signal processing, and particularly relates to a method for extracting radar signal pulse sequences based on cross-correlation and estimated signal-to-noise ratio. Background Art

[0002] Radar is widely used in many fields such as military, aerospace, meteorological monitoring, and traffic management. Especially in the military field, as an important carrier of electronic information, the accurate identification and positioning of the radiation characteristics of radar signals play a crucial role in military strategies, tactical deployments, and command decisions. The radar sampling signal not only contains valid pulses but also a lot of complex noises, and the key information in the signal exists in the valid pulses. Therefore, extracting the valid pulses in the radar signal sequence is a crucial task.

[0003] Traditional methods for extracting valid pulses generally directly set a threshold to identify the starting point of the pulse. If the signal can remain above the threshold for a period of time, the current pulse is considered a valid pulse. This method has great limitations and errors, and cannot accurately separate the noise and valid pulses. At the same time, it may extract interference signals that have nothing to do with the target pulse.

[0004] Existing methods for extracting valid pulses all use some methods to smooth the signal, such as using short-time energy, taking the envelope, filters, etc., which reduces the influence of noise on the extraction of valid pulses. In these methods, whether using empirical thresholds or adaptive thresholds, a unique static threshold is determined based on prior knowledge or the statistical characteristics of the entire pulse sequence. However, in practical applications, especially in the case of dynamically changing channel conditions, these static thresholds often cannot guarantee the accuracy and reliability of all pulse extractions, resulting in the loss of transient information for some of the extracted pulses. And in radar signals, transients are an important part of the signal characteristics. Therefore, this limitation of the existing methods will lead to information loss, thus affecting the accuracy of ranging and identification and the data integrity of communication transmission. Summary of the Invention

[0005] The present invention provides a method for extracting radar signal pulse sequences based on cross-correlation and estimated signal-to-noise ratio, which can more accurately identify the starting and ending points of valid pulses, has strong anti-noise and anti-interference capabilities, high extraction accuracy, and is applicable to real-time extraction of valid pulses in multiple scenarios.

[0006] An embodiment of the present invention provides a method for extracting radar signal pulse sequences based on cross-correlation and estimated signal-to-noise ratio, including the following steps:

[0007] Step S101, perform frame division on the sampling signal, and calculate the product sequence of the short-time energy and the zero-crossing rate of each frame;

[0008] Step S102: Determine the length of a single pulse according to the sampling rate and pulse width of the sampling signal, and construct a rectangular wave in combination with the frame shift;

[0009] Step S103: Perform cross-correlation calculation on the rectangular wave and the product sequence of the short-time energy and zero-crossing rate of the sampling signal to obtain a cross-correlation result;

[0010] Step S104: Segment the sampling signal according to the cross-correlation result;

[0011] Step S105: Select a segment of noise in the segmented signal as the reference noise, and calculate the estimated signal-to-noise ratio of the pulse;

[0012] Step S106: Frame the segmented signal and perform noise normalization processing;

[0013] Step S107: Detect the starting point and ending point of the pulse in the segmented signal after noise normalization according to the estimated signal-to-noise ratio of the pulse.

[0014] Optionally, in an embodiment of the present invention, in step S101, the sampling signal is the time-domain received signal X(t), and the sampling signal after framing using the framing function is:

[0015]

[0016] where, x i represents the i-th frame signal, N is the frame length, K is the total number of frames after framing, t0 is the first sampling time point, and t is the time;

[0017] The short-time energy of each frame is:

[0018]

[0019] The zero-crossing rate of each frame is:

[0020]

[0021] where, sgn(x) is the sign function;

[0022] The product sequence of the short-time energy and the zero-crossing rate is:

[0023] EZ x [t] = E x [t] · Z x [t].

[0024] Optionally, in an embodiment of the present invention, in step S102, the rectangular wave is:

[0025]

[0026] Among them, A is the amplitude of the rectangular wave, t is the time, and L is the length of the product sequence of the short-time energy and the zero-crossing rate after single-pulse framing, which is expressed as:

[0027]

[0028] Among them, Fs is the sampling rate, Pw is the pulse width, and M is the frame shift.

[0029] Optionally, in an embodiment of the present invention, in step S103, the cross-correlation result is:

[0030]

[0031] Among them, ∑ t EZ x (t) is the product sequence of the short-time energy and the zero-crossing rate of the sampling signal, Y(t + l) is the rectangular wave, t is the time, l is the delay amount, and R(l) is the cross-correlation value between EZ x (t) and Y(t) at a delay of l.

[0032] Optionally, in an embodiment of the present invention, in step S104, it specifically includes the following steps:

[0033] Step S201, traverse all the positive peak points in the cross-correlation result R(l), and the positive peak point is the best matching position of the pulse and the rectangular wave Y(t);

[0034] Step S202, calculate the corresponding position P1 of the rectangular wave Y(t) in the product sequence EZ x [t] of the short-time energy and the zero-crossing rate;

[0035] Step S203, calculate the corresponding position P2 of the position P1 in the sampling signal X(t), and the position where P2 is located is a segmented signal S(t), which includes an effective pulse and some noise before and after the pulse.

[0036] Optionally, in an embodiment of the present invention, in step S105, the reference noise is:

[0037] Noise = {x1, x2, …, x n}

[0038] Among them, x1, x2, …, x n are the first n points in the segmented signal S(t), and n < 0.5L;

[0039] The estimated signal-to-noise ratio of the pulse is:

[0040]

[0041] Among them, L0 is the length of the segmented signal S(t).

[0042] Optionally, in an embodiment of the present invention, in step S106, the frame length of the frame division of the segmented signal S(t) is the same as the length n of the reference noise Noise, and the segmented signal after frame division is:

[0043]

[0044] Among them, N0 is the frame length, and K0 is the number of frames after frame division;

[0045] The segmented signal after noise normalization processing is:

[0046]

[0047] Optionally, in an embodiment of the present invention, in step S107, according to the estimated signal-to-noise ratio SNR of the pulse, the start point and end point of the pulse are detected in the segmented signal S2(t) after noise normalization, including:

[0048] Step S301, traverse the segmented signal S2(t) after noise normalization processing, and find the previous point Q1 of the first point greater than the estimated signal-to-noise ratio SNR of the pulse and the next point Q2 of the last point greater than the estimated signal-to-noise ratio SNR of the pulse;

[0049] Step S302, calculate the corresponding position points Q3 and Q4 of point Q1 and point Q2 in the segmented signal S(t);

[0050] Step S303, extract the pulse P(t) between point Q3 and point Q4, and determine whether the error between its length and the theoretical single pulse length is within a preset range. If so, save P(t) as an effective pulse, otherwise discard it.

[0051] The method for extracting a radar signal pulse sequence based on cross-correlation and estimated signal-to-noise ratio in the embodiment of the present invention performs cross-correlation calculation on the product sequence of the short-time energy and zero-crossing rate of a specifically constructed rectangular wave and a sampling signal to obtain all segmented signals containing effective pulses and part of the noise before and after the pulses. Then, the estimated signal-to-noise ratio of the effective pulses in the segmented signal is calculated, and the start point and end point of the effective pulses are detected in the segmented signal after noise normalization. The present invention extracts effective pulses in two steps. According to the real-time noise environment of the pulse and combined with the estimated signal-to-noise ratio, it accurately identifies the start point and end point of the effective pulses without relying on threshold setting, and can avoid extraction errors caused by improper threshold setting; at the same time, it has strong adaptability to channel uncertainty and environmental changes, and can still maintain a high extraction accuracy in a dynamically changing complex environment.

[0052] Additional aspects and advantages of the present invention will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the present invention. Brief Description of the Drawings

[0053] The above and / or additional aspects and advantages of the present invention will become apparent and be readily understood from the following description of embodiments in conjunction with the accompanying drawings, in which:

[0054] Figure 1 It is a flowchart of a method for extracting a radar signal pulse sequence based on cross - correlation and estimated signal - to - noise ratio according to an embodiment of the present invention;

[0055] Figure 2 It is a construction diagram of a rectangular wave according to an embodiment of the present invention;

[0056] Figure 3 It is a cross - correlation result diagram according to an embodiment of the present invention;

[0057] Figure 4 It is a flowchart of signal segmentation according to an embodiment of the present invention;

[0058] Figure 5 It is a positive peak point recognition result diagram according to an embodiment of the present invention;

[0059] Figure 6 It is the position of the rectangular wave corresponding to the positive peak point in the product of short - time energy and zero - crossing rate according to an embodiment of the present invention;

[0060] Figure 7 It is the position of the rectangular wave corresponding to the positive peak point in the sampled signal according to an embodiment of the present invention;

[0061] Figure 8 It is a segmented signal diagram according to an embodiment of the present invention;

[0062] Figure 9 It is a flowchart for identifying the start and end points of valid pulses according to an embodiment of the present invention. Detailed Description of the Embodiments

[0063] Embodiments of the present invention will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are intended to explain the present invention, and should not be construed as limiting the present invention.

[0064] Figure 1 It is a flowchart of a method for extracting a radar signal pulse sequence based on cross - correlation and estimated signal - to - noise ratio according to an embodiment of the present invention.

[0065] As Figure 1As shown in the figure, the method for extracting radar signal pulse sequences based on cross-correlation and estimated signal-to-noise ratio includes the following steps:

[0066] Step S101: Perform frame division on the sampled signal and calculate the product sequence of the short-time energy and zero-crossing rate of each frame.

[0067] The signal obtained by receiver sampling is generally a time-domain signal, which contains noise and effective pulses. In the embodiments of the present invention, the receiver samples the chirp signal at a preset sampling rate Fs, the pulse width is set to Pw, and the sampled signal is denoted as X(t). It should be noted that this chirp signal is transmitted by the transmitter through the wireless channel. Therefore, the noise in X(t) obtained by receiver sampling has randomness and time-variability, which conforms to the signal acquisition in the actual application scenario.

[0068] In the embodiments of the present invention, the frame division function for X(t) is:

[0069] x i = X[t0 + i·M:t0 + i·M + N - 1], i = 0, 1, …, K - 1

[0070] where, x i represents the i-th frame signal, N is the frame length, M is the frame shift, K is the total number of frames, and t0 is the first sampling time point. It should be noted that there are no strict restrictions and requirements for the frame length and frame shift used for frame division. The reference setting condition is that the frame shift is approximately equal in length to the transient part of the effective pulse, and the frame length is set to twice the frame shift. Practice has proved that when the length of the transient part of the effective pulse cannot be determined, the smaller the frame length is set, the higher the resolution, the higher the pulse extraction accuracy, and the greater the computational amount; the larger the frame length is set, the lower the resolution, the lower the pulse extraction accuracy, and the smaller the computational amount. Therefore, in actual applications, it is necessary to comprehensively measure the settings of the frame length and frame shift according to the pulse length and the requirements for extraction accuracy.

[0071] The X(t) after frame division can be expressed as:

[0072]

[0073] where, t is the time, and K is the number of frames after frame division of X(t);

[0074] The short-time energy of each frame is expressed as:

[0075]

[0076] The zero-crossing rate of each frame is expressed as:

[0077]

[0078] where, sgn(x) is the sign function;

[0079] The product sequence of short-time energy and zero-crossing rate is expressed as:

[0080] EZ x [t]=E x [t]·Z x [t].

[0081] Step S102: Determine the length of a single pulse according to the sampling rate and pulse width of the sampling signal, and construct a rectangular wave in combination with the frame shift.

[0082] The rectangular wave is composed of sinusoidal waves with equal amplitude. Its characteristic is that the high-level and low-level durations in one period are equal, and the waveform is symmetric. It should be noted that the high-level duration of the constructed rectangular wave should be approximately equal to the length of a valid pulse in x EZ, and the combination of its high level and low level needs to strictly meet the ratio of 1:2:1, as Figure 2 shown. In this embodiment, the rectangular wave can be expressed as:

[0083]

[0084] where A is the amplitude of the rectangular wave, t is the time, and L is the length of the product sequence of short-time energy and zero-crossing rate after the single pulse is segmented in step S101, which is expressed as:

[0085]

[0086] where Fs is the sampling rate, Pw is the pulse width, and M is the frame shift.

[0087] Step S103: Perform cross-correlation calculation on the rectangular wave and the product sequence of the short-time energy and zero-crossing rate of the sampling signal to obtain the cross-correlation result.

[0088] In the embodiment of the present invention, the cross-correlation result is expressed as:

[0089]

[0090] where t is the time, l is the delay amount, and R(l) is the cross-correlation value between EZ x (t) and Y(t) at a delay of l.

[0091] Step S104: Segment the sampling signal according to the cross-correlation result.

[0092] The high-level duration of the rectangular wave is approximately the same as the length of the product sequence of the short-time energy and zero-crossing rate of a single valid pulse. When the two coincide highly, the cross-correlation result shows a peak, as Figure 3 shown. In this embodiment, the method for segmenting the sampling signal is as Figure 4As shown in the figure, it includes:

[0093] Step S201: Traverse all positive peak points in the cross-correlation result R(l), as Figure 5 shown in the figure. The position at this point is the optimal matching position of the pulse and the rectangular wave Y(t);

[0094] Step S202: Calculate the corresponding position P1 of the rectangular wave Y(t) in the product sequence EZ x [t] of short-time energy and zero-crossing rate according to the positive peak points, as Figure 6 shown in the figure;

[0095] Step S203: Calculate the corresponding position P2 of the position P1 in the sampling signal X(t), as Figure 7 shown in the figure; The position where P2 is located is a segmented signal S(t), which includes a valid pulse and part of the noise before and after the pulse, as Figure 8 shown in the figure.

[0096] Step S105: Select a section of noise in the segmented signal as the reference noise, and calculate the estimated signal-to-noise ratio of the pulse.

[0097] In the embodiment of the present invention, the selected reference noise is expressed as:

[0098] Noise = {x1, x2, …, x n}

[0099] where x1, x2, …, x n are the first n points in S(t), and n < 0.5L;

[0100] The estimated signal-to-noise ratio of the pulse is expressed as:

[0101]

[0102] where L0 is the length of S(t).

[0103] Step S106: Frame the segmented signal and perform noise normalization processing.

[0104] In the embodiment of the present invention, the frame length of the framed segmented signal S(t) is the same as the length n of the reference noise Noise obtained in step S105. The framed segmented signal is expressed as:

[0105]

[0106] where N0 is the frame length and K0 is the number of frames after framing;

[0107] The segmented signal after noise normalization processing is expressed as:

[0108]

[0109] Step S107: Detect the start point and end point of the pulse in the segmented signal after noise normalization according to the estimated signal-to-noise ratio of the pulse.

[0110] In an embodiment of the present invention, the start point and end point of the pulse are detected in the segmented signal S2(t) after noise normalization according to the estimated signal-to-noise ratio SNR of the pulse, as Figure 9 shown, including:

[0111] Step S301: Traverse the segmented signal S2(t) after noise normalization processing, and find the previous point Q1 of the first point greater than the estimated signal-to-noise ratio SNR of the pulse and the next point Q2 of the last point greater than the estimated signal-to-noise ratio SNR of the pulse;

[0112] Step S302: Calculate the corresponding positions Q3 and Q4 of Q1 and Q2 in the segmented signal S(t);

[0113] Step S303: Extract the pulse P(t) between Q3 and Q4, and determine whether its length is approximately equal to the theoretical single pulse length. If so, save P(t) as an effective pulse, otherwise discard it.

[0114] According to the radar signal pulse sequence extraction method based on cross-correlation and estimated signal-to-noise ratio proposed in the embodiment of the present invention, first, the sampled signal is framed, the product sequence of the short-time energy and the zero-crossing rate of each frame is calculated, and a rectangular wave is constructed according to the single pulse length and the frame shift. Then, the signal sequence is segmented according to the cross-correlation result of the rectangular wave and the product sequence, and each segment contains an effective pulse and the noise before and after the pulse. Subsequently, the effective pulse in each segment is accurately extracted: a section of noise is taken in front of the segment, the estimated signal-to-noise ratio of the pulse is calculated, and the entire sequence is subjected to noise normalization processing. Finally, the start point and end point of the pulse are detected according to the value of the estimated signal-to-noise ratio. This method does not depend on threshold setting, avoids extraction errors caused by improper threshold setting, and has a small amount of computation and strong practicability, and can quickly and accurately extract radar pulses in multiple scenarios.

[0115] In the description of this specification, the description referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0116] In addition, the terms "first" and "second" are used only for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of such features. In the description of the present invention, the meaning of "N" is at least two, such as two, three, etc., unless otherwise specifically defined.

[0117] Any process or method description shown in a flowchart or described in other ways herein can be understood to represent a module, segment, or portion of code including one or N executable instructions for implementing a customized logic function or process, and the scope of the preferred embodiments of the present invention includes additional implementations, where the functions can be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present invention pertain.

Claims

1. A method for extracting radar signal pulse sequences based on cross-correlation and estimated signal-to-noise ratio, characterized in that, It includes the following steps: Step S101: Perform frame segmentation on the sampled signal, and calculate the product sequence of the short-time energy and zero-crossing rate of each frame; Step S102: Determine the length of a single pulse according to the sampling rate and pulse width of the sampled signal, and construct a rectangular wave in combination with the frame shift; Step S103: Perform cross-correlation calculation between the rectangular wave and the product sequence of the short-time energy and zero-crossing rate of the sampled signal to obtain a cross-correlation result; Step S104: Segment the sampled signal according to the cross-correlation result; Step S105: Select a segment of noise in the segmented signal as the reference noise, and calculate the estimated signal-to-noise ratio of the pulse; Step S106: Perform frame segmentation on the segmented signal and perform noise normalization processing; Step S107: Detect the start point and end point of the pulse in the segmented signal after noise normalization according to the estimated signal-to-noise ratio of the pulse.

2. The method according to claim 1, characterized in that, In step S101, the sampled signal is the time-domain received signal X(t), and the sampled signal after frame segmentation using the frame segmentation function is: where x i represents the i-th frame signal, N is the frame length, K is the total number of frames after frame division, t0 is the first sampling time point, and t is the time; The short-time energy of each frame is: The zero-crossing rate of each frame is: where sgn(x) is the sign function; The product sequence of the short-time energy and zero-crossing rate is: EZ x [t] = E x [t]·Z x [t].

3. The method according to claim 1, wherein In step S102, the rectangular wave is: where A is the amplitude of the rectangular wave, t is the time, and L is the length of the product sequence of the short-time energy and zero-crossing rate after frame segmentation of a single pulse, expressed as: where Fs is the sampling rate, Pw is the pulse width, and M is the frame shift.

4. The method according to claim 1, wherein In step S103, the cross-correlation result is: Among them, ∑ t EZ x (t) is the product sequence of the short-time energy and the zero-crossing rate of the sampling signal, Y(t + l) is a rectangular wave, t is time, l is the delay amount, and R(l) is the cross-correlation value between EZ x (t) and Y(t) at a delay of l.

5. The method according to claim 1, wherein In step S104, it specifically includes the following steps: Step S201: Traverse all positive peak points in the cross-correlation result R(l), and the positive peak point is the best matching position of the pulse and the rectangular wave Y(t); Step S202, calculate the corresponding position P1 of the rectangular wave Y(t) in the product sequence EZ x [t] of the short-time energy and the zero-crossing rate according to the positive peak point; Step S203: Calculate the corresponding position P2 of the position P1 in the sampled signal X(t), and the position where P2 is located is a segmented signal S(t), which includes an effective pulse and part of the noise before and after the pulse.

6. The method according to claim 1, wherein In step S105, the reference noise is: Noise={x1,x2,…,x n} where x1, x2, …, x n are the first n points in the segmented signal S(t), and n < 0.5L; The estimated signal-to-noise ratio of the pulse is: where L0 is the length of the segmented signal S(t).

7. The method according to claim 1, wherein In step S106, the frame length of the frame segmentation of the segmented signal S(t) is the same as the length n of the reference noise Noise, and the segmented signal after frame segmentation is: where N0 is the frame length and K0 is the number of frames after frame segmentation; The segmented signal after noise normalization processing is:

8. The method according to claim 1, wherein In step S107, detecting the start point and end point of the pulse in the segmented signal S2(t) after noise normalization according to the estimated signal-to-noise ratio SNR of the pulse includes: Step S301: Traverse the segmented signal S2(t) after noise normalization processing, and find the previous point Q1 of the first point greater than the estimated signal-to-noise ratio SNR of the pulse and the next point Q2 of the last point greater than the estimated signal-to-noise ratio SNR of the pulse; Step S302: Calculate the corresponding position points Q3 and Q4 of the point Q1 and the point Q2 in the segmented signal S(t); Step S303: Extract the pulse P(t) between the point Q3 and the point Q4, and determine whether the error between its length and the theoretical single pulse length is within the preset range. If so, save P(t) as an effective pulse, otherwise discard it.

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