An Interval Adaptive Signal Detection Method and System Based on Digital Channelized Receiver

Abstract

This invention proposes an interval adaptive signal detection method and system based on a digital channelized receiver, belonging to the field of signal detection in passive radar. It addresses the problem that existing digital channelized receivers, during passive radar signal reception, suffer from signal aliasing with broadband noise and unequal power gain across different frequency bands, leading to the inability to properly detect the channelized signal. This invention designs a filter bank, performs serial-to-parallel conversion on the input data, and performs IFFT and CORDIC operations on the filtered K-channel output data to obtain the amplitude and phase information of M signals. Then, it performs m-point autocorrelation accumulation on the amplitudes of the M signals. Simultaneously, it provides a more flexible threshold calculation method and refines the operating and signal detection bandwidth of the channelized receiver, offering a new solution to improve the adaptive signal detection performance of digital channelized receivers. This invention is applicable to signal detection in scenarios with uneven interference and gain distribution within the receiver's operating bandwidth.

Description

Technical Field

[0001] This invention belongs to the field of signal detection in passive radar, specifically a signal detection method based on a digital channelized receiver and applicable to scenarios with uneven interference and gain distribution within the receiver's operating bandwidth. Background Technology

[0002] A digital channelized receiver is a device that decomposes a broadband signal into multiple narrowband sub-channels, achieving efficient signal processing and analysis through digital processing technology. It is widely used in radar, electronic warfare, and communications monitoring. This type of receiver utilizes digital signal processing technology to divide the received broadband signal into several frequency sub-bands. This design allows for the simultaneous monitoring or processing of signals across multiple frequency bands, improving spectrum utilization, system flexibility, and the detection probability of radar signals.

[0003] Signal detection is of great significance in the field of passive radar and has wide applications in electronic warfare, communications, and other areas. With the advancement of radar technology, the surveillance bandwidth and noise levels in the operating environment of passive radar have increased significantly, posing a major challenge to the extraction of pulse information. Current methods for setting signal detection thresholds in digital channelized receivers calculate threshold values ​​based on the signal strength of each channel within the entire receiver's processing bandwidth, using these thresholds to extract pulse signals from each channel. However, in actual operation, the processing bandwidth of passive radar can reach over 10 GHz. Signals in different frequency bands have varying gains after down-conversion to the signal processing frequency band. When these signals are down-converted and spliced ​​to the channelized receiver for processing, the noise floor amplitude in some adjacent channels will be significantly higher than that in other channels. Furthermore, when radar pulse signals are mixed with broadband noise, the noise levels of different channels within the receiver's processing bandwidth vary. Therefore, signal detection thresholds set based on the entire operating bandwidth cannot simultaneously accommodate signal detection in the frequency range covered by broadband noise and other frequency domain ranges.

[0004] In summary, digital channelized receivers can effectively extract characteristic information from passive radar received signals. This is beneficial not only for selecting multiple targets but also for assessing target threat levels and understanding the battlefield situation. However, during passive radar signal reception, issues such as signal aliasing with broadband noise and unequal power gains across different frequency bands can arise, leading to problems where the channelized signal cannot be detected normally. Therefore, how to perform signal detection more flexibly and effectively is an urgent challenge that needs to be addressed. Summary of the Invention

[0005] This invention addresses the problem that existing digital channelized receivers, during passive radar signal reception, suffer from signal aliasing with broadband noise and unequal power gains across different frequency bands, resulting in the inability to properly detect the channelized signal.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] This invention introduces an interval adaptive signal detection method into a digital channelized receiver. Using this method, the false alarm probability of the digital channelized receiver can be reduced even when the signal is mixed with broadband noise and the power gain varies across different frequency bands. The interval adaptive signal detection method based on a digital channelized receiver proposed in this invention includes the following steps:

[0008] Step S1: Based on the number of sub-channels in uniform channelization Determine the number of valid channels And design a prototype filter. The cutoff frequency and the minimum order of the filter are calculated. Complete the filter bank structure design;

[0009] Step S2: Convert the AD input signal to 1: Double string-to-parallel transformation, and The signal is delayed by one clock cycle and then combined with the newly input signal to form a circuit. Parallel signals;

[0010] Step S3: Transform the prototype filter The coefficients are distributed equally to Road Each relative filter coefficient is double-interpolated by 0, thus improving the input... Convolution of parallel signals yields filtered output. ;

[0011] Step S4: Filter the output Perform IFFT operations, and process odd and even paths separately, outputting... Road data correspondence The IQ components of each effective channel signal;

[0012] Step S5: For CORDIC calculation is performed on the IQ components of the signal to obtain... The amplitude and phase information of the signal;

[0013] Step S6: For The amplitude of the road signal is Point autocorrelation accumulation;

[0014] Step S7: Set the detection threshold and detection interval, compare the autocorrelation accumulation result with the detection threshold, and complete the pulse detection of the effective narg signal;

[0015] Step S8: Measure the frequency and pulse width of the control signal by detecting the effective narg signal, select the channel based on the frequency measurement result, output the pulse parameters, and assemble them into a PDW for subsequent processing.

[0016] Furthermore, the aforementioned filter bank has a structure with 50% overlap between adjacent channels.

[0017] Furthermore, the aforementioned filter bank includes one low-pass filter. and Bandpass filters .

[0018] Furthermore, step S1 above specifically includes:

[0019] Step S11: Based on the number of sub-channels in uniform channelization and AD sampling frequency Determine the sub-channel bandwidth as and processing bandwidth ;

[0020] Step S12: Design a low-pass filter using the equiripple method, and set the passband cutoff frequency of the filter to be... The stopband start frequency is The passband ripple is 0.1dB, and the stopband attenuation is 60dB.

[0021] Furthermore, the above-mentioned odd and even paths are processed as follows: the output of the even path is multiplied by -1 every clock cycle, and the output of the odd path is delayed by one clock cycle.

[0022] Furthermore, step S7 above specifically includes:

[0023] Step S71: Set the detection threshold Time Each adjacent channel constitutes a detection interval, and channels within the same detection interval use the same detection threshold. ;

[0024] Step S72: Set the register-type variable to When the signal amplitude is greater than the threshold value, n1 is set to 1; when the signal amplitude is less than the threshold value, n1 is set to 0.

[0025] Step S73: ... The values ​​are passed sequentially. When the result of ANDing all register variables is 1, the pulse is considered valid, and the narg signal is pulled high when the pulse is valid. When the result of ORing all register variables is 0, the pulse ends and the narg signal returns to zero.

[0026] Furthermore, step S8 above specifically includes:

[0027] When the pulse is valid, multi-point phase difference frequency measurement is performed on the signal, and the pulse leading frequency is latched. The pulse duration is counted by a timer, the pulse width is calculated, the channel is selected based on the frequency measurement results, the pulse parameters are output, and a PDW is formed for subsequent processing.

[0028] The interval adaptive signal detection method based on a digital channelized receiver described in this invention can be entirely implemented using computer software. Therefore, correspondingly, this invention also provides an interval adaptive signal detection system based on a digital channelized receiver. The system includes a storage device, which is used to execute the interval adaptive signal detection method and steps based on a digital channelized receiver proposed above.

[0029] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the interval adaptive signal detection method based on a digital channelized receiver as described above.

[0030] The present invention also provides a computer device, which includes a memory and a processor. The memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes the interval adaptive signal detection method based on a digital channelized receiver described in any one of the above-mentioned methods.

[0031] The beneficial effects of this invention are as follows:

[0032] 1. Compared with existing technologies, this invention aims to provide an interval adaptive signal detection method suitable for digital channelized receivers. When the receiver front-end processes broadband signals, signals from different gain frequency bands are down-converted and spliced ​​into the digital channelized receiver, resulting in some adjacent channels having different noise floor intensities. Furthermore, when radar pulse signals are mixed with broadband noise, the noise levels of each channel within the receiver's processing bandwidth are different, making normal signal detection impossible. This method effectively solves the problem of increased false alarm probability in signal detection when different frequency bands within the receiver's operating bandwidth have different noise floor amplitudes, provides a more flexible threshold calculation method, refines the operating and signal detection bandwidths of the channelized receiver, and offers a new solution for improving the adaptive signal detection performance of digital channelized receivers.

[0033] 2. The interval adaptive signal detection method proposed in this invention can effectively solve the problem of excessively high false alarm probability caused by different noise floor amplitudes in different frequency bands within the working bandwidth of digital channelized receivers. It greatly reduces the number of false pulses, reduces the workload of subsequent sorting in the receiver, and has important practical engineering value.

[0034] Furthermore, the interval adaptive signal detection method proposed in this invention is applicable to the situations described in the background art and can reduce the false alarm probability of digital channelized receivers. By further refining the signal detection frequency band interval without changing the receiver's operating bandwidth, the adaptive capability of the threshold and the receiver's signal detection capability are effectively improved.

[0035] This invention is applicable to signal detection in scenarios with interference and uneven gain distribution within the receiver's operating bandwidth. Attached Figure Description

[0036] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0037] Figure 1 This is a structural diagram of the 50% overlap filter bank between adjacent channels proposed in this invention;

[0038] Figure 2 It is the data sequence after equivalent serial-to-parallel transformation as described in this invention;

[0039] Figure 3 This is the digital channelized receiver structure described in this invention;

[0040] Figure 4 It is the interval adaptive signal detection threshold described in this invention. Detailed Implementation

[0041] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted so as not to obscure the description of this application with unnecessary detail.

[0042] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the present invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention.

[0043] Implementation Method 1: This implementation method introduces an interval adaptive signal detection method into a digital channelized receiver. Using this method, the false alarm probability of the digital channelized receiver can be reduced under conditions of signal aliasing with broadband noise and unequal power gains across different frequency bands. The interval adaptive signal detection method based on a digital channelized receiver proposed in this implementation method includes the following steps:

[0044] Step S1: Based on the number of sub-channels in uniform channelization Determine the number of valid channels And design a prototype filter. The cutoff frequency and the minimum order of the filter are calculated. Complete the filter bank structure design;

[0045] Step S2: Convert the AD input signal to 1: Double string-to-parallel transformation, and The signal is delayed by one clock cycle and then combined with the newly input signal to form a circuit. Parallel signals;

[0046] Step S3: Transform the prototype filter The coefficients are distributed equally to Road Each relative filter coefficient is double-interpolated by 0, thus improving the input... Convolution of parallel signals yields filtered output. ;

[0047] Step S4: Filter the output Perform IFFT operations, and process odd and even paths separately, outputting... Road data correspondence The IQ components of each effective channel signal;

[0048] Step S5: For CORDIC calculation is performed on the IQ components of the signal to obtain... The amplitude and phase information of the signal;

[0049] Step S6: For The amplitude of the road signal is Point autocorrelation accumulation;

[0050] Step S7: Set the detection threshold and detection interval, compare the autocorrelation accumulation result with the detection threshold, and complete the pulse detection of the effective narg signal;

[0051] Step S8: Measure the frequency and pulse width of the control signal by detecting the effective narg signal, select the channel based on the frequency measurement result, output the pulse parameters, and assemble them into a PDW for subsequent processing.

[0052] Because existing receiver front-ends process broadband signals, down-converted and spliced ​​signals from different gain frequency bands are input to the digital channelized receiver, resulting in some adjacent channels having different noise floor intensities. Furthermore, when radar pulse signals are mixed with broadband noise, the noise levels of each channel within the receiver's processing bandwidth differ, making signal detection impossible. Therefore, this embodiment proposes an interval-adaptive signal detection method suitable for digital channelized receivers. This method effectively solves the problem of increased false alarm probability when different frequency bands within the receiver's operating bandwidth have varying noise floor amplitudes. It also provides a more flexible threshold calculation method, refines the operating and signal detection bandwidths of the channelized receiver, and sets detection thresholds based on the noise floor intensity of each detection interval, reducing the false alarm probability. This provides a new solution for improving the adaptive signal detection performance of digital channelized receivers.

[0053] Implementation Method 2, see below Figures 1 to 4 This embodiment describes a specific method for interval adaptive signal detection based on a digital channelized receiver, as proposed in the above embodiments.

[0054] Step S1: Based on the number of sub-channels in uniform channelization Determine the number of valid channels And design a prototype filter. The cutoff frequency and the minimum order of the filter are calculated. Complete the filter bank structure design;

[0055] Specifically:

[0056] Let the number of sub-channels in uniform channelization be . According to the bandpass sampling theorem and The spectrum about Symmetry, therefore choose Frequency range division of effective channel number One, and thus design the corresponding filter.

[0057] Design a prototype filter based on the AD sampling frequency and the receiver's operating bandwidth. Find the cutoff frequency and calculate the minimum order of the filter. Specifically: Let the number of sub-channels in uniform channelization be... AD sampling frequency is The sub-channel bandwidth is Processing bandwidth is A low-pass filter is designed using the equiripple method, and the passband cutoff frequency of the filter is set to [value missing]. The stopband start frequency is Given a passband ripple of 0.1dB and a stopband attenuation of 60dB, calculate the minimum order of the filter. And filter coefficients.

[0058] Furthermore, since practical filters cannot achieve sharp cutoff, in order to achieve full frequency coverage within the monitoring bandwidth, save multiplier resources, filtering time, and reduce the filter order, this embodiment is designed as follows: Figure 1 The filter bank structure shown has 50% overlap between adjacent channels. (Example) Figure 1 As shown, the filter cannot achieve sharp cutoff in actual implementation, so a 50% overlap structure is used to cover the receiver's operating bandwidth. Because of the frequency domain overlap of the filter, a single-frequency signal will gain in both adjacent channels, and channel selection ultimately needs to be based on frequency measurement results.

[0059] Step S2: Convert the AD input signal to 1: Double string-to-parallel transformation, and The signal is delayed by one clock cycle and then combined with the newly input signal to form a circuit. Parallel signals;

[0060] Specifically:

[0061] Since the data input to the digital channelized receiver needs to undergo delay differential processing to match the channelization structure input conditions for the remaining steps, the AD input signal needs to be processed. Let the data sequence output by the AD sampling be... ,but go through The data sequence after multiple extractions is ,back Parallel data compared to the previous The data path is delayed by one clock cycle, and the equivalent serial-to-parallel conversion is as follows: Figure 2 As shown.

[0062] Step S3: Transform the prototype filter The coefficients are distributed equally to Road Each relative filter coefficient is double-interpolated by 0, thus improving the input... Convolution of parallel signals yields filtered output. ;

[0063] Specifically:

[0064] The filter bank includes one low-pass filter. and Bandpass filters , prototype filter The coefficients are distributed equally to Road Each relative filter coefficient is interpolated by a factor of 2 to zero for the input. The signal is convolved to obtain the filtered output. .

[0065] For example:

[0066] analog signal The discrete-time signal is sampled by the ADC and output. The input is fed into the filter bank, the filter bank's first... The output of each sub-band for

[0067]

[0068] Step S4: Filter the output Perform IFFT operations, and process odd and even paths separately, outputting... Road data correspondence The IQ components of each effective channel signal;

[0069] Specifically:

[0070] For filtering Path output Perform an IFFT operation, multiplying the even-numbered outputs by -1 every clock cycle, and delaying the odd-numbered outputs by one clock cycle to align them with the even-numbered outputs. The outputs... Road data correspondence The IQ components of an effective channel signal.

[0071] For example:

[0072] The output of the bandpass filter It needs to be multiplied by a complex exponential transform to baseband and then... Double extraction.

[0073] The frequency response of the k-th filter is:

[0074] prototype filter Polyphase representation is:

[0075]

[0076] Among them, multiphase components , ( (Round up). Substituting this into the frequency response expression, we get:

[0077]

[0078] The signal passes through the first Bandpass filters The output is the result of performing an IDFT transform on the signal after it has been filtered by multiphase components. To reduce the computational load, [the following is used:] The decimation-in-time operation is moved before the polyphase filter, and the IDFT operation is replaced by the fast IFFT algorithm. The resulting digital channelized receiver structure is as follows: Figure 3 As shown. Figure 3 The analysis in step 4 shows that the channelized output is equivalent to the result of filtering the serial-to-parallel transformed signal, performing IFFT operation, and processing the odd and even paths separately.

[0079] Step S5: For CORDIC calculation is performed on the IQ components of the signal to obtain... The amplitude and phase information of the signal;

[0080] Specifically:

[0081] After the AD sampling signal is channelized, the output is an in-phase quadrature baseband signal. and Its amplitude is extracted using the CORDIC algorithm. With phase information

[0082]

[0083] Step S6: For The amplitude of the road signal is Point autocorrelation accumulation;

[0084] Specifically:

[0085] The amplitude of the output signal is measured Point autocorrelation accumulation operation, after channelization, the signal-to-noise ratio is The autocorrelation cumulative output signal-to-noise ratio is derived as follows:

[0086]

[0087] Step S7: Set the detection threshold and detection interval, compare the autocorrelation accumulation result with the detection threshold, and complete the pulse detection of the effective narg signal;

[0088] Specifically:

[0089] In the signal detection process, taking the common Rayleigh distribution interference as an example, the constant false alarm rate (CFAR) performance of the receiver is analyzed. The interference signal satisfies...

[0090]

[0091]

[0092] in, For noise variance, The number of reference units, and has Find the normally distributed random variable The probability density function is:

[0093]

[0094] Normalized variables are The probability density distribution is obtained as follows:

[0095]

[0096] The new random variable has a mean of The variance is Gaussian distribution can be used to calculate the false alarm rate.

[0097]

[0098] False alarm probability can be calculated The statistical average is

[0099]

[0100] This formula shows that the statistical average of the false alarm probability is only related to the number of reference units. Related to threshold It is related to the function.

[0101] Digital channelized receivers treat the autocorrelation accumulation result of each channel's signal as a reference unit. For non-uniformly distributed interference signals in the frequency domain, due to the varying interference signal strength within each reference unit, the estimated average value is underestimated when the detection point is located in a strong interference region and some reference units are located in a weak interference region, leading to an increased false alarm probability. Conversely, when the detection point is located in a weak interference region and some reference units are located in a strong interference region, the estimated average value is overestimated, resulting in an excessively high threshold. Although the false alarm probability decreases, the effective signal detection rate also decreases. This analysis also applies to situations with different frequency band gains.

[0102] For a digital channelized receiver, the number of reference elements Furthermore, with a fixed channel bandwidth, if a uniform threshold decision coefficient is used, fluctuations will occur due to the estimated mean of interference deviating from the statistical mean, increasing the likelihood that the amplitude of the interference signal will exceed the threshold. If the threshold coefficient is updated in real time, the receiver implementation will be limited by FPGA resources and the real-time requirements of signal processing.

[0103] Based on the above analysis, the number of units When the bandwidth is too large, the detection bandwidth will cover different interference or gain ranges, causing the false alarm probability and detection probability indicators of the receiver to fail to meet the requirements. In order to solve this problem, this implementation further decomposes the working bandwidth of the channelized receiver into multiple detection bandwidth calculation thresholds for signal detection.

[0104] Specifically:

[0105] Calculate threshold At that time, the receiver's operating bandwidth is divided into ( There are ) intervals, each interval has In a channeled digital channelized receiver with no signal input, the sampled data is noise, whose probability density function follows a Gaussian distribution. The probability density function of the signal envelope follows a Rayleigh distribution. The false alarm probability can be expressed as...

[0106]

[0107] in, The threshold is obtained by transforming the signal envelope amplitude. The expression is

[0108]

[0109] Under constant false alarm rate (CFAR) detection conditions, the threshold for amplitude detection. The value of is determined solely by the noise variance. Signal amplitude detection threshold for each interval Set to:

[0110]

[0111] in, It is the first The amplitude of the sub-channel input signal, It is the threshold coefficient. It is the noise floor. In the formula, within the detection interval... The average amplitude of the sub-channel signal changes dynamically with the amplitude of the input signal. When the input signal is in one sub-channel but other sub-channels contain only noise, the mean of each channel component within the detection interval is higher than the noise amplitude but lower than the input signal amplitude. When all channels within the detection interval contain only noise, it cannot be guaranteed that the mean will be greater than all noise components; therefore, the cumulative mean of the autocorrelation of each channel must be multiplied by a threshold coefficient. Plus noise floor It is used to detect signals and extract pulses.

[0112] To prevent false pulses caused by individual peak points exceeding the detection threshold, thus increasing the false alarm probability, the signal undergoes secondary detection. The decision pulse is considered valid when all points exceed (or fall below) the detection threshold. The interval adaptive signal detection threshold setting is as follows: Figure 4 As shown. Figure 4 The results show that the interval adaptive signal detection method further differentiates the receiver's operating bandwidth and sets the detection threshold according to the noise floor intensity of each detection interval, thereby reducing the probability of false alarms.

[0113] Specifically:

[0114] Set detection threshold Time Each adjacent channel constitutes a detection interval, and channels within the same detection interval use the same detection threshold. Signal autocorrelation accumulation result and detection threshold Compare and set register variables When the signal amplitude is greater than the threshold value, n1 is set to 1; when the signal amplitude is less than the threshold value, n1 is set to 0. The values ​​are passed sequentially. When the result of ANDing all register variables is 1, the pulse is considered valid, and the narg signal is pulled high when the pulse is valid. When the result of ORing all register variables is 0, the pulse ends and the narg signal returns to zero.

[0115] Step S8: Measure the frequency and pulse width of the control signal by detecting the effective narg signal, select the channel based on the frequency measurement result, output the pulse parameters, and assemble them into a PDW for subsequent processing.

[0116] Specifically:

[0117] When the pulse is valid, multi-point phase difference frequency measurement is performed on the signal, and the pulse leading-edge frequency is latched. The pulse duration is counted by a timer to calculate the pulse width. Channel selection is performed based on the frequency measurement results, and pulse parameters are output to form a PDW (Power-On-Demand) for subsequent processing.

[0118] This embodiment proposes an interval adaptive signal detection method suitable for digital channelized receivers. This method effectively solves the problem of increased false alarm probability in signal detection when the noise floor amplitude varies across different frequency bands within the receiver's operating bandwidth. It provides a more flexible threshold calculation method and refines the operating and signal detection bandwidths of the channelized receiver, offering a new solution for improving the adaptive signal detection performance of digital channelized receivers.

[0119] Implementation Method 3: The interval adaptive signal detection method for digital channelized receivers proposed in the above implementation methods can be entirely implemented using computer software. Therefore, correspondingly, this implementation method proposes an interval adaptive signal detection system for digital channelized receivers, the system comprising:

[0120] Used to determine the number of sub-channels based on uniform channelization Determine the number of valid channels And design a prototype filter. The cutoff frequency and the minimum order of the filter are calculated. A storage device that completes the design of the filter bank structure;

[0121] Used to convert the AD input signal to 1: Double string-to-parallel transformation, and The signal is delayed by one clock cycle and then combined with the newly input signal to form a circuit. A storage device for parallel signals;

[0122] Used to transform prototype filter The coefficients are distributed equally to Road Each relative filter coefficient is double-interpolated by 0, thus improving the input... Convolution of parallel signals yields filtered output. Storage device;

[0123] Used for filtering output Perform IFFT operations, and process odd and even paths separately, outputting... Road data correspondence Storage device for the IQ components of each effective channel signal;

[0124] Used for CORDIC calculation is performed on the IQ components of the signal to obtain... A storage device for the amplitude and phase information of the signal;

[0125] Used for The amplitude of the road signal is A storage device for point autocorrelation accumulation;

[0126] A storage device for setting detection thresholds and detection intervals, comparing autocorrelation accumulation results with detection thresholds, and completing pulse detection of valid narg signals;

[0127] This device is used for frequency pulse width measurement of signals controlled by pulse detection effective narg signals, channel selection based on frequency measurement results, outputting pulse parameters, and forming a storage device for PDW for subsequent processing.

[0128] Implementation Method 4: This implementation method provides a computer-readable storage medium storing a computer program. When the computer program is run by a processor, it executes the interval adaptive signal detection method based on a digital channelized receiver as described in any one of Implementation Methods 1 to 2 above.

[0129] Implementation Method 5: This implementation method provides a computer device, which includes a memory and a processor. The memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes the interval adaptive signal detection method based on a digital channelized receiver as described in any one of Implementation Methods 1 to 2 above.

[0130] This embodiment provides a computer device, the hardware of which is a general-purpose model and is not shown in the figure. The system includes a processor and a memory, which can be connected by a bus or other means. The memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs and modules, as well as corresponding program instructions / modules. The processor executes various functional applications and data processing by running the non-transitory software programs, instructions and modules stored in the memory, so as to realize the interval adaptive signal detection method and steps based on the digital channelized receiver in the above method embodiment.

[0131] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0132] The above description is merely an embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention should be included within the scope of the claims of the present invention.

Claims

1. A method for interval adaptive signal detection based on a digital channelized receiver, characterized in that, The method is as follows: S1: Based on the number of sub-channels in uniform channelization Determine the number of valid channels And design a prototype filter. The cutoff frequency and the minimum order of the filter are calculated. Complete the filter bank structure design; S2: Convert the AD input signal to step 1: Double string-to-parallel transformation, and The signal is delayed by one clock cycle and then combined with the newly input signal to form a circuit. Parallel signals; S3: Transform the prototype filter The coefficients are distributed equally to Road Each relative filter coefficient is double-interpolated by 0, thus improving the input... Convolution of parallel signals yields filtered output. ; S4: Filter the output Perform IFFT operations, and process odd and even paths separately, outputting... Road data correspondence The IQ components of each effective channel signal; S5: Yes CORDIC calculation is performed on the IQ components of the signal to obtain... The amplitude and phase information of the signal; S6: Yes The amplitude of the road signal is Point autocorrelation accumulation; S7: Set the detection threshold and detection interval, compare the autocorrelation accumulation result with the detection threshold, and complete the pulse detection of the effective narg signal; Specifically: Calculate threshold At that time, the receiver's operating bandwidth is divided into There are intervals, each interval has... One channel, When there is no signal input to the digital channelized receiver, the sampled data is noise, and its probability density function follows a Gaussian distribution. The probability density function of the signal envelope follows a Rayleigh distribution. The false alarm probability is expressed as: in, The threshold is obtained by transforming the signal envelope amplitude. The expression is: Under constant false alarm rate (CFAR) detection conditions, the threshold for amplitude detection. The value of is determined solely by the noise variance, the th Signal amplitude detection threshold for each interval Set to: in, It is the first The amplitude of the sub-channel input signal, It is the threshold coefficient. It is the noise floor, where the detection interval is within the formula. The average amplitude of the sub-channel signal changes dynamically with the amplitude of the input signal. When the input signal is in one sub-channel but other sub-channels only contain noise, the mean of each channel component within the detection interval is higher than the noise amplitude but lower than the input signal amplitude. When all channels within the detection interval contain only noise, it cannot be guaranteed that the mean is greater than all noise components. Therefore, the cumulative mean of the autocorrelation of each channel must be multiplied by a threshold coefficient. Plus noise floor It is used to detect signals and extract pulses; To prevent false pulses caused by individual peak points exceeding the detection threshold, thus increasing the false alarm probability, the signal undergoes secondary detection. When all points exceed the detection threshold, the validity of the pulse is determined; the interval adaptive signal detection method further differentiates the receiver's operating bandwidth and sets the detection threshold according to the noise floor intensity of each detection interval to reduce the probability of false alarms. Specifically: Set detection threshold Time Each adjacent channel constitutes a detection interval, and channels within the same detection interval use the same detection threshold. Signal autocorrelation accumulation result and detection threshold Compare and set register variables When the signal amplitude is greater than the threshold value, n1 is set to 1; when the signal amplitude is less than the threshold value, n1 is set to 0. The values ​​are passed sequentially. When the result of the AND operation of all register variables is 1, the pulse is considered valid, and the narg signal is pulled high when the pulse is valid. When the result of the OR operation of all register variables is 0, the pulse ends and the narg signal returns to zero. S8: The frequency and pulse width of the control signal are measured by detecting the effective narg signal of the pulse. The channel is selected based on the frequency measurement result, and the pulse parameters are output to form a PDW for subsequent processing.

2. The interval adaptive signal detection method based on a digital channelized receiver according to claim 1, characterized in that, The filter bank has a structure with 50% overlap between adjacent channels.

3. The interval adaptive signal detection method based on a digital channelized receiver according to claim 1, characterized in that, The filter bank includes one low-pass filter. and Bandpass filters .

4. The interval adaptive signal detection method based on a digital channelized receiver according to claim 3, characterized in that, S1 specifically refers to: S11: Based on the number of sub-channels in uniform channelization and AD sampling frequency Determine the sub-channel bandwidth as and processing bandwidth ; S12: Design a low-pass filter using the equiripple method, and set the passband cutoff frequency of the filter to be... The stopband start frequency is The passband ripple is 0.1dB, and the stopband attenuation is 60dB.

5. The interval adaptive signal detection method based on a digital channelized receiver according to claim 1, characterized in that, The odd and even paths are handled separately as follows: the output of the even path is multiplied by -1 every clock cycle, and the output of the odd path is delayed by one clock cycle.

6. The interval adaptive signal detection method based on a digital channelized receiver according to claim 1, characterized in that, S8 specifically refers to: When the pulse is valid, multi-point phase difference frequency measurement is performed on the signal, and the pulse leading frequency is latched. The pulse duration is counted by a timer, the pulse width is calculated, the channel is selected based on the frequency measurement results, the pulse parameters are output, and a PDW is formed for subsequent processing.

7. An interval adaptive signal detection system based on a digital channelized receiver, characterized in that, The system includes a storage device for performing the method of claim 1.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the interval adaptive signal detection method based on a digital channelized receiver as described in any one of claims 1-6.

9. A computer device, characterized in that, The device includes a memory and a processor. The memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes the interval adaptive signal detection method based on a digital channelized receiver as described in any one of claims 1-6.

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