Method for extracting radar signal pulse sequences based on cross-correlation and estimated signal-to-noise ratio

Abstract

The application discloses a radar signal pulse sequence extraction method based on cross-correlation and estimated signal-to-noise ratio, and belongs to the field of radar signal processing. The method first frames the sampling signal, calculates the product sequence of the short-time energy and the zero-crossing rate of each frame, and constructs a rectangular wave 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 segment of noise is taken in front of the segment, the estimated signal-to-noise ratio of the pulse is calculated, the whole sequence is subjected to noise normalization processing, and finally the starting point and the ending point of the pulse are detected according to the value of the estimated signal-to-noise ratio. The method does not depend on threshold setting, avoids the extraction error caused by improper threshold setting, has small operation amount, high practicability, and can quickly and accurately extract the radar pulse in multiple scenes.

Description

Technical Field

[0001] This invention relates to the field of radar signal processing technology, and in particular to a method for extracting radar signal pulse sequences based on cross-correlation and signal-to-noise ratio estimation. Background Technology

[0002] Radar is widely used in various fields such as military, aerospace, meteorological monitoring, and traffic management. Especially in the military field, radar signals, as an important electronic information carrier, play a crucial role in the accurate identification and location of their radiation characteristics for military strategy, tactical deployment, and command decisions. Radar sampling signals contain not only effective pulses but also a lot of complex noise. The key information in the signal is contained in the effective pulses, so extracting the effective pulses from the radar signal sequence is a crucial task.

[0003] Traditional methods for extracting valid pulses typically involve setting a threshold to identify the pulse's start point. If the signal remains above the threshold for a certain period, the pulse is considered valid. This method has significant limitations and errors; it cannot accurately separate noise from valid pulses and may also extract interference signals unrelated to the target pulse.

[0004] Existing effective pulse extraction methods all employ signal smoothing techniques, such as using short-time energy, envelope extraction, and filters, to reduce the impact of noise on effective pulse extraction. In these methods, whether empirical or adaptive thresholds are used, a unique static threshold is determined based on prior knowledge or the statistical characteristics of the entire pulse sequence. However, in practical applications, especially under dynamically changing channel conditions, these static thresholds often cannot guarantee the accuracy and reliability of all pulse extractions, leading to the loss of transient information in some extracted pulses. In radar signals, transients are a crucial component of signal characteristics. Therefore, this limitation of existing methods results in information loss, affecting the accuracy of ranging and identification, as well as the integrity of data transmitted in communication. Summary of the Invention

[0005] This invention provides a radar signal pulse sequence extraction method based on cross-correlation and signal-to-noise ratio estimation. It can more accurately identify the start and end points of effective pulses, has strong anti-noise and interference capabilities, high extraction accuracy, and is suitable for real-time effective pulse extraction in multiple scenarios.

[0006] This invention provides a method for extracting radar signal pulse sequences based on cross-correlation and signal-to-noise ratio estimation, comprising the following steps:

[0007] Step S101: Perform frame segmentation on the sampled signal and calculate the product sequence of short-time energy and zero-crossing rate for each frame;

[0008] Step S102: Determine the length of a single pulse based on the sampling rate and pulse width of the sampled signal, and construct a rectangular wave by combining it with frame shift;

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

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

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

[0012] Step S106: The segmented signal is divided into frames and noise normalization is performed.

[0013] Step S107: Detect the start and end points of the pulse in the noise-normalized segments based on the estimated signal-to-noise ratio of the pulse.

[0014] Optionally, in one embodiment of the present invention, in step S101, the sampling signal is a time-domain received signal. The sampled signal after framing using the framing function is as follows:

[0015]

[0016] in, Indicates the first Frame signal, For frame length, This represents the total number of frames after framing. For the first sampling time point, For time;

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

[0018]

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

[0020]

[0021] in, It is a symbolic function;

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

[0023] .

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

[0025]

[0026] in, The amplitude of the rectangular wave. For time, The length of the sequence of short-time energy and zero-crossing rate products after framing a single pulse is expressed as:

[0027]

[0028] in, Sampling rate, M is the pulse width, and M is the frame shift.

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

[0030]

[0031] in, It is a sequence of the product of the short-time energy and the zero-crossing rate of the sampled signal. It is a rectangular wave. For time, It is the delay amount. It is delayed for hour and The cross-correlation value.

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

[0033] Step S201: Traverse the cross-correlation results All positive peak points are points where the pulse and the rectangular wave are located. The best matching position;

[0034] Step S202: Calculate the rectangular wave based on the positive peak point. The product sequence of the short-time energy and the zero-crossing rate The corresponding position P1 in the text;

[0035] Step S203, calculate position P1 in the sampled signal The corresponding position P2 in the signal is a segmented signal. This includes a valid pulse and some pre- and post-pulse noise.

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

[0037]

[0038] in, Segmented signal Center front One point, 0.5L;

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

[0040]

[0041] in, Segmented signal The length.

[0042] Optionally, in one embodiment of the present invention, in step S106, the segmented signal Frame length and reference noise length Similarly, the segmented signal after framing is as follows:

[0043]

[0044] in, For frame length, This represents the number of frames after framing.

[0045] The segmented signal after noise normalization is:

[0046] .

[0047] Optionally, in one embodiment of the present invention, in step S107, the estimated signal-to-noise ratio of the pulse is determined. Segmented signal after noise normalization The start and end points of the detection pulse include:

[0048] Step S301: Traverse the segmented signals after noise normalization processing. Find the first estimated signal-to-noise ratio greater than the pulse. The estimated signal-to-noise ratio of the point preceding Q1 and the last pulse greater than the given pulse. The point following the point Q2;

[0049] Step S302, calculate points Q1 and Q2 in the segmented signal The corresponding positions are points Q3 and Q4 in the diagram;

[0050] Step S303: Extract the pulse between point Q3 and point Q4. It then determines whether the error between its length and the theoretical single pulse length is within a preset range; if so, it saves the result. If it is an effective pulse, otherwise discard it.

[0051] This invention discloses a radar signal pulse sequence extraction method based on cross-correlation and estimated signal-to-noise ratio (SNR). The method calculates the cross-correlation of a specific constructed rectangular wave with the product sequence of the short-time energy and zero-crossing rate of the sampled signal to obtain segmented signals containing all effective pulses and some pre- and post-pulse noise. It then calculates the estimated SNR of the effective pulses in each segmented signal and detects the start and end points of the effective pulses within the noise-normalized segmented signals. This invention extracts effective pulses in two steps. Based on the real-time noise environment of the pulses and the estimated SNR, it accurately identifies the start and end points of the effective pulses, without relying on threshold settings, thus avoiding extraction errors caused by improper threshold settings. Furthermore, it exhibits strong adaptability to channel uncertainties and environmental changes, maintaining high extraction accuracy even in dynamically changing and complex environments.

[0052] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

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

[0054] Figure 1 This is a flowchart illustrating a radar signal pulse sequence extraction method based on cross-correlation and signal-to-noise ratio estimation according to an embodiment of the present invention;

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

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

[0057] Figure 4 This is a flowchart illustrating the signal segmentation process according to an embodiment of the present invention.

[0058] Figure 5 This is a diagram showing the positive peak point identification results of an embodiment of the present invention;

[0059] Figure 6 The positive peak point of this embodiment of the invention corresponds to the rectangular wave position in the product of short-time energy and zero-crossing rate;

[0060] Figure 7 This refers to the position of the positive peak point in the sampled signal corresponding to the rectangular wave in this embodiment of the invention.

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

[0062] Figure 9 This is a flowchart illustrating the identification process for the effective pulse start and end points in an embodiment of the present invention. Detailed Implementation

[0063] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein 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 with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0064] Figure 1 This is a flowchart illustrating a radar signal pulse sequence extraction method based on cross-correlation and signal-to-noise ratio estimation according to an embodiment of the present invention.

[0065] like Figure 1 As shown, the radar signal pulse sequence extraction method based on cross-correlation and signal-to-noise ratio estimation includes the following steps:

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

[0067] The signal sampled by the receiver is generally a time-domain signal, which includes noise and valid pulses. In embodiments of the present invention, the receiver uses a preset sampling rate. The linear frequency modulated signal is sampled, and the pulse width is set to... The sampled signal is denoted as It should be noted that this linear frequency modulated signal is transmitted by the transmitter through a wireless channel. Therefore, the signal sampled by the receiver... The noise in the signal is random and time-varying, which is consistent with the signal acquisition in real-world application scenarios.

[0068] In an embodiment of the present invention, for The framing function for performing frame division is:

[0069]

[0070] in, For frame length, For frame shift, Total number of frames This is the first sampling time point. It should be noted that there are no strict limitations or requirements on the frame length and frame shift used for framing. A general rule of thumb is that the frame shift should be approximately equal in length to the transient portion of the effective pulse, and the frame length should be twice the frame shift. Practice has shown that when the length of the transient portion of the effective pulse cannot be determined, a smaller frame length results in higher resolution and higher pulse extraction accuracy, but also a greater computational load; conversely, a larger frame length results in lower resolution, lower pulse extraction accuracy, but a smaller computational load. Therefore, in practical applications, the settings for frame length and frame shift should be comprehensively considered based on the pulse length and extraction accuracy requirements.

[0071] After framing It can be represented as:

[0072]

[0073] in, For time, for The number of frames after framing;

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

[0075]

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

[0077]

[0078] in, It is a symbolic function;

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

[0080] .

[0081] Step S102: Determine the length of a single pulse based on the sampling rate and pulse width of the sampled signal, and construct a rectangular wave by combining it with frame shift.

[0082] A rectangular wave consists of equal-amplitude sine waves, characterized by equal durations of high and low levels within one cycle, and a symmetrical waveform. It should be noted that the high-level duration of the constructed rectangular wave should be equal to... The length of a valid pulse is approximately equal to the number of pulses in the sequence, and the combination of its high and low levels must strictly satisfy a 1:2:1 ratio, such as... Figure 2 As shown. In this embodiment, the rectangular wave can be represented as:

[0083]

[0084] in, The amplitude of the rectangular wave. For time, The length of the sequence of short-time energy and zero-crossing rate products after framing a single pulse in step S101 is expressed as:

[0085]

[0086] in, Sampling rate, M is the pulse width, and M is the frame shift.

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

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

[0089]

[0090] in, For time, It is the delay amount. It is delayed for hour and The cross-correlation value.

[0091] Step S104: Segment the sampled signal according to the cross-correlation results.

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

[0093] Step S201: Traverse the cross-correlation results All positive peak points, such as Figure 5 As shown, this point represents both a pulse and a rectangular wave. Optimal matching position;

[0094] Step S202: Calculate the rectangular wave based on the positive peak point. In the product sequence of short-time energy and zero-crossing rate The corresponding position P1 in, such as Figure 6 As shown;

[0095] Step S203: Calculate position P1 in the sampled signal The corresponding position P2 in, such as Figure 7 As shown; the location of P2 is a segmented signal. This includes a valid pulse and some pre- and post-pulse noise, such as Figure 8 As shown.

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

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

[0098]

[0099] in, for Center front One point, 0.5L;

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

[0101]

[0102] in, for The length.

[0103] Step S106: The segmented signal is divided into frames and noise normalization is performed.

[0104] In an embodiment of the present invention, segmented signals... The frame length of the segment and the reference noise obtained in step S105 length Similarly, the segmented signal after framing is represented as follows:

[0105]

[0106] in, For frame length, This represents the number of frames after framing.

[0107] The segmented signal after noise normalization is represented as follows:

[0108] .

[0109] Step S107: Detect the start and end points of the pulse in the noise-normalized segments based on the estimated signal-to-noise ratio of the pulse.

[0110] In embodiments of the present invention, based on the estimated signal-to-noise ratio of the pulse... Segmented signal after noise normalization The start and end points of the detection pulse, such as Figure 9 As shown, it includes:

[0111] Step S301: Traverse the segmented signal after noise normalization processing Find the first estimated signal-to-noise ratio greater than the pulse. The estimated signal-to-noise ratio of the point preceding Q1 and the last pulse greater than the given value. The point following the point Q2;

[0112] Step S302: Calculate Q1 and Q2 in the segmented signal The corresponding positions are Q3 and Q4;

[0113] Step S303: Extract the pulse between Q3 and Q4 And determine whether its length is approximately equal to the theoretical length of a single pulse; if so, save it. If it is an effective pulse, otherwise discard it.

[0114] The radar signal pulse sequence extraction method based on cross-correlation and estimated signal-to-noise ratio (SNR) proposed in this invention first divides the sampled signal into frames, calculates the product sequence of short-time energy and zero-crossing rate for each frame, and constructs a rectangular wave based on the length of a single pulse and the frame shift. Then, the signal sequence is segmented according to the cross-correlation result between the rectangular wave and the product sequence, with each segment containing one effective pulse and noise before and after the pulse. Subsequently, the effective pulse in each segment is accurately extracted: a noise segment is taken before the segment, the estimated SNR of the pulse is calculated, and the entire sequence is normalized for noise. Finally, the start and end points of the pulse are detected based on the estimated SNR value. This method does not rely on threshold settings, avoiding extraction errors caused by improper threshold settings. Furthermore, this method has low computational complexity, high practicality, and can quickly and accurately extract radar pulses in multiple scenarios.

[0115] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0116] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0117] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.

Claims

1. A method for extracting radar signal pulse sequences based on cross-correlation and signal-to-noise ratio estimation, characterized in that, Includes the following steps: Step S101: Perform frame segmentation on the sampled signal and calculate the product sequence of short-time energy and zero-crossing rate for each frame; Step S102: Determine the length of a single pulse based on the sampling rate and pulse width of the sampled signal, and construct a rectangular wave by combining it with frame shift; Step S103: Perform cross-correlation calculation on the product sequence of the rectangular wave and the sampled signal's short-time energy and zero-crossing rate to obtain the cross-correlation result; Step S104 involves segmenting the sampled signal based on the cross-correlation result; step S104 specifically includes the following steps: Step S201: Traverse the cross-correlation results All positive peak points are points where the pulse and the rectangular wave are located. The best matching position; Step S202: Calculate the rectangular wave based on the positive peak point. The product sequence of the short-time energy and the zero-crossing rate The corresponding position P1 in the text; Step S203, calculate position P1 in the sampled signal The corresponding position P2 in the signal is a segmented signal. This includes a valid pulse and some pre- and post-pulse noise; Step S105: Select a segment of noise from the segmented signal as the reference noise and calculate the estimated signal-to-noise ratio of the pulse; Step S106: The segmented signal is divided into frames and noise normalization is performed. Step S107: Detect the start and end points of the pulse in the noise-normalized segments based on the estimated signal-to-noise ratio of the pulse. In step S107, based on the estimated signal-to-noise ratio of the pulse... Segmented signal after noise normalization The start and end points of the detection pulse include: Step S301: Traverse the segmented signals after noise normalization processing. Find the first estimated signal-to-noise ratio greater than the pulse. The estimated signal-to-noise ratio of the point preceding Q1 and the last pulse greater than the given pulse. The point following the point Q2; Step S302, calculate points Q1 and Q2 in the segmented signal The corresponding positions are points Q3 and Q4 in the diagram; Step S303: Extract the pulse between point Q3 and point Q4. It then determines whether the error between its length and the theoretical single pulse length is within a preset range; if so, it saves the result. If it is an effective pulse, otherwise discard it.

2. The method according to claim 1, characterized in that, In step S101, the sampling signal is a time-domain received signal. The sampled signal after framing using the framing function is as follows: in, Indicates the first Frame signal, For frame length, This represents the total number of frames after framing. For the first sampling time point, For time; The short-time energy of each frame is: The zero-crossing rate for each frame is: in, It is a symbolic function; The product sequence of short-time energy and zero-crossing rate is as follows: 。 3. The method according to claim 1, characterized in that, In step S102, the rectangular wave is: in, The amplitude of the rectangular wave. For time, The length of the sequence of short-time energy and zero-crossing rate products after framing a single pulse is expressed as: in, Sampling rate, M is the pulse width, and M is the frame shift.

4. The method according to claim 1, characterized in that, In step S103, the cross-correlation result is: in, It is a sequence of the product of the short-time energy and the zero-crossing rate of the sampled signal. It is a rectangular wave. For time, It is the delay amount. It is delayed for hour and The cross-correlation value.

5. The method according to claim 1, characterized in that, In step S105, the reference noise is: in, Segmented signal Center front One point, 0.5L; The estimated signal-to-noise ratio of the pulse is: in, Segmented signal The length.

6. The method according to claim 1, characterized in that, In step S106, the segmented signal Frame length and reference noise length Similarly, the segmented signal after framing is as follows: in, For frame length, This represents the number of frames after framing. The segmented signal after noise normalization is: 。

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