Interval adaptive signal detection method and system based on digital channelized receiver

Abstract

The invention provides an interval adaptive signal detection method and system based on a digital channelized receiver, and belongs to the field of signal detection in passive radars. The problems that in the passive radar signal receiving process of an existing digital channelized receiver, aliasing of signals and broadband noise exists, and power gains of different frequency bands are unequal, so that channelized signals cannot be normally detected are solved. The amplitude and phase information of M paths of signals are obtained by designing a filter bank, performing multiple serial-parallel conversion processing on input data and performing IFFT operation and CORDIC operation on data output by filtering K paths, then m-point self-correlation accumulation is performed on the amplitude of the M paths of signals, and the amplitude and phase information of the M paths of signals is obtained. Meanwhile, a more flexible threshold calculation method is provided, the working and signal detection bandwidth of the channelized receiver is refined, and a new scheme is provided for improving the signal detection adaptivity of the digital channelized receiver. The method is suitable for signal detection in a scene with non-uniform interference and gain distribution in the working bandwidth of the receiver.

Description

Technical Field

[0001] The present invention belongs to the field of signal detection in passive radar, and specifically relates to a signal detection method based on a digital channelized receiver and applicable to a scenario where interference and gain distribution are uneven within the operating bandwidth of the receiver. Background Art

[0002] A digital channelized receiver is a device that decomposes a broadband signal into multiple narrow sub-channels and realizes efficient processing and analysis of signals through digital processing technology. It is widely used in fields such as radar, electronic warfare, and communication monitoring. This receiver uses digital signal processing technology to divide the received broadband signal into several frequency sub-bands. Such a design allows for simultaneous monitoring or processing of signals in multiple frequency bands, improving the spectrum utilization rate, system flexibility, and the detection probability of radar signals.

[0003] The problem of signal detection is of great significance in the field of passive radar and has wide applications in fields such as electronic countermeasures and communication. With the progress of radar technology, the surveillance bandwidth of passive radar and the noise level in the working environment have increased significantly, which poses a huge challenge to the extraction of pulse information by passive radar. Currently, the method for setting the signal detection threshold of a digital channelized receiver is to calculate the threshold value based on the intensity of signals in each channel within the entire receiver processing bandwidth, and extract the pulse signals in each channel using this threshold. However, in actual operation of the receiver, the processing bandwidth of passive radar can reach more than 10 G, and the gains of signals in different frequency bands after down-conversion to the signal processing frequency band are not equal. When they are spliced through down-conversion and processed by the channelized receiver, the noise floor amplitudes in some adjacent channels will be significantly higher than those in the remaining channels. Moreover, when radar pulse signals are mixed with broadband noise, the noise levels in each channel within the receiver processing bandwidth are different, and the signal detection threshold set based on the entire working bandwidth cannot take into account the signal detection in the frequency range covered by broadband noise and the remaining frequency domains.

[0004] In summary, digital channelized receivers can effectively extract the characteristic information of passive radar received signals, which is not only beneficial for sorting multiple targets but also enables the assessment of the threat level of targets by obtaining information and grasping the battlefield situation. However, during the process of passive radar receiving signals, there will be situations where signals are mixed with broadband noise and the power gains in different frequency bands are not equal, resulting in the problem that the channelized signals cannot be detected normally. Therefore, how to perform signal detection more flexibly and effectively is an urgent challenge that needs to be solved. Summary of the Invention

[0005] The present invention is used to solve the problem that in the process of passive radar receiving signals by existing digital channelized receivers, there are situations where signals are mixed with broadband noise and the power gains in different frequency bands are not equal, resulting in the problem that the channelized signals cannot be detected normally.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The present invention introduces an interval adaptive signal detection method into a digital channelized receiver. Using this method can reduce the false alarm probability of digital channelized receiver detection in the case of signal and broadband noise aliasing and unequal power gains in different frequency bands. An interval adaptive signal detection method based on a digital channelized receiver proposed by the present invention includes the following steps:

[0008] Step S1: Determine the effective channel number M according to the number of sub-channels K of uniform channelization, design the cut-off frequency of the prototype filter h0(n) and calculate the minimum order N of the filter, and complete the design of the filter bank structure;

[0009] Step S2: Perform a 1:M times serial-to-parallel transformation on the AD input signal, and delay the M-channel signals by one clock and then form K-channel parallel signals with the newly input signal;

[0010] Step S3: Average the coefficients of the prototype filter h0(n) and distribute them to K channels to obtain P = [N / K], and insert 0 twice for each relative filter coefficient, so as to perform convolution on the input K-channel parallel signals to obtain the filtered output y k (n);

[0011] Step S4: Perform an IFFT operation on the filtered output y k (n), and process the odd and even channels separately. The output K-channel data correspond to the IQ components of M effective channel signals;

[0012] Step S5: Perform a CORDIC operation on the IQ components of the M-channel signals to obtain the amplitude and phase information of the M-channel signals;

[0013] Step S6: Perform m-point autocorrelation accumulation on the amplitudes of the M-channel signals;

[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: Control the frequency pulse width measurement of the signal by the pulse detection effective narg signal, perform channel selection according to the frequency measurement result, output the pulse parameters, and form a PDW for subsequent processing.

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

[0017] Furthermore, the above filter bank includes 1 low-pass filter h0[n] and K - 1 band-pass filters h k [n].

[0018] Further, the above-mentioned step S1 is specifically as follows:

[0019] Step S11: According to the number of sub-channels K of uniform channelization and the AD sampling frequency f s , determine that the sub-channel bandwidth is f s / K and the processing bandwidth is 2f s / K;

[0020] Step S12: Design a low-pass filter using the equiripple method, and set the passband cut-off frequency of the filter to f s / 2K, the stopband starting frequency to f s / K, the passband ripple to 0.1 dB, and the stopband attenuation to 60 dB.

[0021] Further, the above-mentioned separate processing of the even and odd paths is specifically as follows: The output of the even path is multiplied by -1 every other clock cycle, and the output of the odd path is delayed by one clock cycle.

[0022] Further, the above-mentioned step S7 is specifically as follows:

[0023] Step S71: Set the detection threshold V T When, use L adjacent channels as a detection interval, and the channels within the same detection interval use the same detection threshold V Tl ;

[0024] Step S72: Set register-type variables as n1, n2,..., n x , set n1 to 1 when the signal amplitude is greater than the threshold value, and set n1 to 0 when the signal amplitude is less than the threshold value;

[0025] Step S73: Transfer the values of n1, n2,..., n x sequentially in a pipelined manner. When the logical AND result of all register variables is 1, the pulse is considered valid, and the pulse detection valid narg signal is pulled high; when the logical OR result of all register variables is 0, the pulse ends, and the narg signal is reset to zero.

[0026] Further, the above-mentioned step S8 is specifically as follows:

[0027] When the pulse is valid, perform multi-point phase difference frequency measurement on the signal, latch the frequency at the pulse front edge; use a timer to count the pulse duration, calculate the pulse width, perform channel selection based on the frequency measurement result, output the pulse parameters, and form a PDW for subsequent processing.

[0028] The interval adaptive signal detection method based on a digital channelized receiver described in the present invention can be entirely implemented by computer software. Correspondingly, the present 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 above-mentioned interval adaptive signal detection method and steps based on a digital channelized receiver.

[0029] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by a processor, it executes the interval adaptive signal detection method based on a digital channelized receiver described in any one of the above.

[0030] The present invention also provides a computer device, which includes a memory and a processor. A computer program is stored in the memory. 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.

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

[0032] 1. Compared with the prior art, the present invention aims to provide an interval adaptive signal detection method applicable to a digital channelized receiver. When the receiver front-end processes broadband signals, signals in different gain frequency bands are down-converted and spliced and input into the digital channelized receiver, and there will be a situation where the noise floor intensities of some adjacent channels are different; and when the radar pulse signal is aliased with broadband noise, the noise levels of each channel within the receiver processing bandwidth are different, and signal detection cannot be carried out normally at this time. This method effectively solves the problem of the increase in the false alarm probability of signal detection in the case of different noise floor amplitudes in different frequency bands within the receiver working bandwidth, provides a more flexible threshold calculation method, refines the working and signal detection bandwidths of the channelized receiver, and provides a new solution for improving the signal detection adaptability of the digital channelized receiver.

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

[0034] Furthermore, the interval adaptive signal detection method proposed by the present invention can be applied to the situation described in the background technology and can reduce the false alarm probability of the digital channelized receiver. Without changing the working bandwidth of the receiver, the signal detection frequency band interval is refined again, effectively improving the adaptive ability of the threshold and the signal detection ability of the receiver.

[0035] The present invention is applicable to signal detection in scenarios where the interference and gain distribution within the operating bandwidth of a receiver are uneven. Description of the Drawings

[0036] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0037] Figure 1 is the structural diagram of the adjacent-channel 50% overlapping filter bank proposed by the present invention;

[0038] Figure 2 is the data sequence after equivalent serial-parallel transformation described in the present invention;

[0039] Figure 3 is the structure of the digital channelized receiver described in the present invention;

[0040] Figure 4 is the interval adaptive signal detection threshold described in the present invention. Specific Embodiments

[0041] In the following description, for the purpose of illustration rather than limitation, specific details such as specific system structures and technologies are proposed to thoroughly understand the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.

[0042] The following further elaborates on the specific embodiments of the present invention in conjunction with the drawings. The following embodiments will help those skilled in the art further understand the present invention, but do not limit the present invention in any form. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several changes and improvements can still be made, and these all fall within the protection scope of the present invention.

[0043] Embodiment 1. In this embodiment, the interval adaptive signal detection method is introduced into the digital channelized receiver. Using this method can reduce the false alarm probability of the digital channelized receiver in the case of signal and broadband noise aliasing and unequal power gains in different frequency bands. A kind of interval adaptive signal detection method based on the digital channelized receiver proposed in this embodiment includes the following steps:

[0044] Step S1: Determine the number of effective channels M according to the number of sub-channels K of uniform channelization, design the cut-off frequency of the prototype filter h0(n) and calculate the minimum order N of the filter to complete the design of the filter bank structure;

[0045] Step S2: Perform a 1:M serial-to-parallel transformation on the AD input signal, and delay the M-channel signals by one clock and then form K-channel parallel signals with the newly input signal;

[0046] Step S3: Evenly distribute the coefficients of the prototype filter h0(n) to K channels to obtain P = [N / K], insert 0 twice for each pair of filter coefficients, and thus perform convolution on the input K-channel parallel signals to obtain the filtered output y k (n);

[0047] Step S4: Perform IFFT operation on the filtered output y k (n), and process the odd and even channels separately. The output K-channel data corresponds to the IQ components of M effective channel signals;

[0048] Step S5: Perform CORDIC operation on the IQ components of the M-channel signals to obtain the amplitude and phase information of the M-channel signals;

[0049] Step S6: Perform m-point autocorrelation accumulation on the amplitudes of the M-channel signals;

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

[0051] Step S8: Control the frequency pulse width measurement of the signal by the pulse detection effective narg signal, perform channel selection according to the frequency measurement result, output the pulse parameters, and form PDW for subsequent processing.

[0052] When the existing receiver front-end processes broadband signals, the signals of different gain frequency bands are down-converted and spliced and input into the digital channelized receiver, and the noise floor intensities of some adjacent channels will be different; and when the radar pulse signal is aliased with broadband noise, the noise levels of each channel within the processing bandwidth of the receiver are different, and signal detection cannot be performed normally at this time. Therefore, this embodiment proposes an interval adaptive signal detection method applicable to digital channelized receivers, which effectively solves the problem of the increase in the false alarm probability of signal detection in the case of different noise floor amplitudes in different frequency bands within the working bandwidth of the receiver. At the same time, it also provides a more flexible threshold calculation method, refines the working and signal detection bandwidths of the channelized receiver, sets the detection threshold according to the noise floor intensity of each detection interval, and reduces the false alarm probability. It provides a new solution for improving the signal detection adaptability of digital channelized receivers.

[0053] Embodiment 2. See Figure 1The following figures illustrate this embodiment, which specifically describes a method for interval adaptive signal detection based on a digital channelized receiver proposed in the above embodiment;

[0054] Step S1: Determine the effective number of channels M according to the number of sub-channels K of uniform channelization, design the cut-off frequency of the prototype filter h0(n), and calculate the minimum order N of the filter to complete the design of the filter bank structure;

[0055] Specifically:

[0056] Assume that the number of sub-channels of uniform channelization is K. According to the band-pass sampling theorem, the spectra of 0 to f s / 2 and f s / 2 to f s are symmetric about f s / 2. Therefore, select the frequency range of f s / 2 to f s to divide the effective number of channels M = K / 2, and thus design the corresponding filter.

[0057] Design the cut-off frequency of the prototype filter h0(n) based on the AD sampling frequency and the receiver operating bandwidth, and calculate the minimum order N of the filter. Specifically: Assume that the number of sub-channels of uniform channelization is K, the AD sampling frequency is f s , the sub-channel bandwidth is f s / K, and the processing bandwidth is 2f s / K. Use the equiripple method to design a low-pass filter, and set the pass-band cut-off frequency of the filter to f s / 2K, the stop-band start frequency to f s / K, the pass-band ripple to 0.1 dB, and the stop-band attenuation to 60 dB, and calculate the minimum order N of the filter and the filter coefficients.

[0058] Furthermore, since the actual filter cannot achieve a sharp cut-off, in order to achieve full coverage of the frequencies within the monitoring bandwidth, save multiplier resources, filtering time, and reduce the filter order, this embodiment designs a filter bank structure with 50% overlap between adjacent channels as shown in Figure 1 . As shown in Figure 1 , the filter cannot achieve a sharp cut-off in the actual implementation process, and a 50% overlap structure is used to cover the receiver operating bandwidth. Because there is frequency-domain overlap in the filter, a single-frequency signal will obtain gain in two adjacent channels, and finally, channel selection needs to be performed according to the frequency measurement result.

[0059] Step S2: Perform a 1:M serial-to-parallel conversion on the AD input signal, and delay the M-channel signal by one clock and combine it with the newly input signal to form K-channel parallel signals;

[0060] Specifically:

[0061] Since the data input to the digital channelized receiver needs to be processed by delay difference to match the input conditions of the channelized structure in the remaining steps, it is necessary to process the AD input signal. Let the data sequence output by AD sampling be x(n), then the data sequence after M-fold decimation of x(n) is x(Mn). The latter M-channel parallel data is delayed by one clock cycle compared to the former M-channel data. The equivalent serial-to-parallel transformation is as Figure 2 shown.

[0062] Step S3: Average the coefficients of the prototype filter h0(n) and distribute them to K channels to obtain P = [N / K]. Insert zeros twice for each pair of filter coefficients, and then convolve the input K-channel parallel signals to obtain the filtered output y k (n);

[0063] Specifically:

[0064] The filter bank includes one low-pass filter h0[n] and K - 1 band-pass filters h k [n]. Average the coefficients of the prototype filter h0(n) and distribute them to K channels to obtain P = [N / K]. Insert zeros twice for each pair of filter coefficients, and convolve the input K-channel signals to obtain the filtered output y k (n).

[0065] For example:

[0066] The analog signal x(t) is sampled by ADC to output the discrete-time signal x(n), which is input to the filter bank. The output y k (n) of the k-th sub-band of the filter bank is

[0067]

[0068] Step S4: Perform IFFT operation on the filtered output y k (n), and process the even and odd channels separately. The output K-channel data corresponds to the IQ components of M effective channel signals;

[0069] Specifically:

[0070] Perform IFFT operation on the filtered K-channel output y k (n). Multiply the output of the even channels by -1 every other clock cycle, and delay the output of the odd channels by one clock cycle to align with the output of the even channels. The output K-channel data corresponds to the IQ components of M effective channel signals.

[0071] For example:

[0072] The output y k (n) of the band-pass filter needs to be multiplied by a complex exponential to transform to the baseband and then decimated by M.

[0073] The frequency response of the k-th filter is: The polyphase representation of the prototype filter h0[n] is as follows:

[0074]

[0075] where the polyphase component P = [N / K] (rounded up). Substituting into the frequency response expression, we get:

[0076]

[0077] The output of the signal passing through the k-th bandpass filter h k (n) is the result of performing the IDFT transformation on the output of the signal after passing through the polyphase component filtering. To reduce the computational complexity, the M-fold decimation is moved forward to before the polyphase filtering, and the IDFT operation is replaced with the fast algorithm IFFT. The resulting digital channelized receiver structure is as Figure 3 shown. Figure 3 It shows that after the analysis in step 4, it is concluded that the channelized output result is equivalent to the result of performing IFFT operation on the signal after filtering the signal after serial-to-parallel conversion and separately processing the odd and even paths.

[0078] Step S5: Perform CORDIC operations on the IQ components of the M-channel signals to obtain the amplitude and phase information of the M-channel signals;

[0079] Specifically:

[0080] After the AD sampling signal completes the channelization process, it outputs the in-phase quadrature baseband signals I(n) and Q(n). The amplitude α(n) and phase information

[0081]

[0082] Step S6: Perform m-point autocorrelation accumulation on the amplitudes of the M-channel signals;

[0083] Specifically:

[0084] Perform m-point autocorrelation accumulation operation on the amplitude of the output signal. The signal-to-noise ratio after channelization is SNR x , and it is derived that the signal-to-noise ratio of the autocorrelation accumulation output is

[0085]

[0086] 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 valid narg signal;

[0087] Specifically:

[0088] In the process of signal detection, taking the common Rayleigh distribution interference as an example, the constant false alarm performance of the receiver is analyzed. The interference signal satisfies

[0089]

[0090] where σ 2 is the noise variance, N is the number of reference cells, and N = M = K / 2. The probability density function of the normally distributed random variable σ N is obtained as follows:

[0091]

[0092] The normalized variable is σ' N = λσ N / σ to obtain the probability density distribution:

[0093]

[0094] The new random variable is a Gaussian distribution with a mean of and a variance of 2Hλ 2 / N. The false alarm rate can be obtained

[0095]

[0096] The false alarm probability P can be calculated fas The statistical average is

[0097]

[0098] It can be seen from this equation that the statistical average of the false alarm probability is only related to the number of reference cells N and the function of the threshold λ.

[0099] The digital channelized receiver regards the autocorrelation accumulation result of the signal in each channel as a reference cell. For the interference signal with non-uniform distribution in the frequency domain, due to the different strengths of the interference signals in the reference cells, when estimating the average value, when the detection point is in the strong interference area and some reference cells are in the weak interference area, the estimated value of the average value is low and the false alarm probability increases; while when the detection point is in the weak interference area and some reference cells are in the strong interference area, the estimated value of the average value is high and the threshold value is raised too high. Although the false alarm probability decreases, the effective signal detection rate also decreases accordingly. This analysis also applies to the case of different frequency band gains.

[0100] For the digital channelized receiver, with the number of reference cells N and the channel bandwidth fixed, if a unified threshold decision coefficient is adopted, due to the deviation of the estimated value of the interference mean from the statistical mean, fluctuations will occur, and the possibility that the amplitude of the interference signal exceeds the threshold increases. If the threshold coefficient is updated in real time, the implementation of the receiver will be restricted by the FPGA resources and the real-time requirements of signal processing.

[0101] According to the above analysis, when the number of units N is too large, the detection bandwidth will cover different interference or gain intervals, resulting in the failure to meet the requirements of the false alarm probability and detection probability indicators of the receiver. To solve this problem, in this embodiment, the working bandwidth of the channelized receiver is further decomposed into multiple detection bandwidth calculation thresholds for signal detection.

[0102] Specifically:

[0103] Calculate the threshold V T When, the working bandwidth of the receiver is divided into L (N = k·L, k ∈ Z + ) intervals, each interval has N / L channels. 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 can be expressed as

[0104]

[0105] where r is the signal envelope amplitude, and the expression for transforming to obtain the threshold V T is

[0106]

[0107] Under the condition of constant false alarm probability detection, the value of the amplitude detection threshold V T is only determined by the noise variance. The signal amplitude detection threshold V Tl of the l-th interval is set as:

[0108]

[0109] where A m [n] is the amplitude of the input signal of the m-th sub-channel, β is the threshold coefficient, and μ is the noise floor. In the formula, the average value of the signal amplitudes of N / L sub-channels in the detection interval changes dynamically with the input signal amplitude. When there is an input signal in the m-th sub-channel and only noise in other sub-channels, the mean value of each channel component in the detection interval is higher than the noise amplitude and lower than the input signal amplitude. When there is only noise in all channels in the detection interval, it cannot be guaranteed that the mean value is greater than all noise components. Therefore, the self-correlation cumulative mean value of each channel is multiplied by the threshold coefficient β and added to the noise floor μ to detect the signal and extract the pulse.

[0110] To prevent false pulses from being generated due to individual peak points exceeding the detection threshold and increasing the false alarm probability, the signal is detected twice. When x consecutive points all exceed (are lower than) the detection threshold, it is determined whether the pulse is valid. The interval adaptive signal detection threshold is set as Figure 4 shown. Figure 4It is shown that the interval adaptive signal detection method further divides the operating bandwidth of the receiver, sets the detection threshold according to the noise floor intensity of each detection interval, and reduces the false alarm probability.

[0111] Specifically:

[0112] Set the detection threshold V T When setting the detection threshold V, take L adjacent channels as a detection interval, and the channels within the same detection interval use the same detection threshold V Tl . Compare the self-correlation accumulation result of the signal with the detection threshold V Tl , and set register-type variables n1, n2,..., n x . When the signal amplitude is greater than the threshold value, set n1 to 1, and when the signal amplitude is less than the threshold value, set n1 to 0. The values of n1, n2,..., n x are passed in sequence. When the logical AND result of all register variables is 1, it is regarded that the pulse is valid, and the pulse detection valid narg signal is pulled high; when the logical OR result of all register variables is 0, the pulse ends, and the narg signal returns to zero.

[0113] Step S8: Control the frequency and pulse width measurement of the signal by the pulse detection valid narg signal, perform channel selection according to the frequency measurement result, output the pulse parameters, and form a PDW for subsequent processing.

[0114] Specifically:

[0115] When the pulse is valid, perform multi-point phase difference frequency measurement on the signal, and latch the frequency at the pulse front edge; use a timer to count the pulse duration to calculate the pulse width. Perform channel selection according to the frequency measurement result, output the pulse parameters, and form a PDW to be sent to the subsequent processing flow.

[0116] This embodiment proposes an interval adaptive signal detection method applicable to a digital channelized receiver. This method effectively solves the problem of increased false alarm probability in signal detection under the condition of different noise floor amplitudes in different frequency bands within the operating bandwidth of the receiver, provides a more flexible threshold calculation method, refines the operating and signal detection bandwidths of the channelized receiver, and provides a new solution for improving the signal detection adaptability of the digital channelized receiver.

[0117] Embodiment 3: The interval adaptive signal detection method applicable to a digital channelized receiver proposed in the above embodiment can be entirely implemented by computer software. Therefore, correspondingly, this embodiment proposes an interval adaptive signal detection system applicable to a digital channelized receiver, and the system includes:

[0118] A storage device for determining the effective number of channels M according to the number of sub-channels K of uniform channelization, designing the cut-off frequency of the prototype filter h0(n), and calculating the minimum order N of the filter to complete the design of the filter bank structure;

[0119] A storage device for performing a 1:M serial-to-parallel conversion on an AD input signal, delaying the M signals by one clock, and forming K parallel signals with newly input signals;

[0120] A storage device for evenly distributing the coefficients of the prototype filter h0(n) to K channels to obtain P = [N / K], inserting zeros twice for each pair of filter coefficients, and thus performing convolution on the input K parallel signals to obtain a filtered output y k (n);

[0121] A storage device for performing an IFFT operation on the filtered output y k (n), separately processing the even and odd channels, and outputting K-channel data corresponding to the IQ components of M effective channel signals;

[0122] A storage device for performing a CORDIC operation on the IQ components of the M signals to obtain the amplitude and phase information of the M signals;

[0123] A storage device for performing m-point autocorrelation accumulation on the amplitudes of the M signals;

[0124] A storage device for setting a detection threshold and a detection interval, comparing the autocorrelation accumulation result with the detection threshold, and completing the pulse detection of the valid narg signal;

[0125] A storage device for controlling the frequency pulse width measurement of a signal by the pulse detection valid narg signal, performing channel selection based on the frequency measurement result, outputting pulse parameters, and forming a PDW for subsequent processing.

[0126] Embodiment 4. This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by a processor, it executes an interval adaptive signal detection method based on a digital channelized receiver described in any one of Embodiments 1 to 2 above.

[0127] Embodiment 5. This embodiment provides a computer device, which includes a memory and a processor. A computer program is stored in the memory. When the processor runs the computer program stored in the memory, the processor executes an interval adaptive signal detection method based on a digital channelized receiver described in any one of Embodiments 1 to 2 above.

[0128] A computer device provided by this embodiment. The hardware device in this part is of a general model and is not shown in the form of a diagram. The system includes a processor and a memory. The processor and the memory can be connected through 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 of the processor by running the non-transitory software programs, instructions, and modules stored in the memory, so as to implement the interval adaptive signal detection method and steps based on the digital channelized receiver in the above method embodiments.

[0129] It should be understood that when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0130] The above are only the embodiments of the present invention and do not limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the scope of the claims of the present invention.

Claims

1. An interval adaptive signal detection method based on a digital channelized receiver, characterized in that, The method is as follows: S1: Determine the effective number of channels M according to the number of sub-channels K of uniform channelization, design the cut-off frequency of the prototype filter h0(n) and calculate the minimum order N of the filter, and complete the design of the filter bank structure; S2: Perform a 1:M serial-to-parallel conversion on the AD input signal, and delay the M-channel signals by one clock and then form K-channel parallel signals with the newly input signal; S3: Evenly distribute the coefficients of the prototype filter h0(n) to K channels to obtain P = [N / K], and insert a zero between every two adjacent filter coefficients. Then, convolve the K-channel parallel input signals to obtain the filtered output y k (n); S4: Perform IFFT operation on the filtered output y k (n), separately process the odd and even paths, and the K-channel data output corresponds to the IQ components of M effective channel signals; S5: Perform CORDIC operations on the IQ components of the M-channel signals to obtain the amplitude and phase information of the M-channel signals; S6: Perform m-point autocorrelation accumulation on the amplitudes of the M-channel signals; 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; S8: Control the frequency pulse width measurement of the signal by the pulse detection of the effective narg signal, perform channel selection based on the frequency measurement result, output the pulse parameters, and form PDW for subsequent processing.

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

3. A method for interval adaptive signal detection based on a digital channelized receiver according to claim 1, characterized in that, The filter bank includes one low-pass filter h0[n] and K-1 band-pass filters h k [n].

4. The interval adaptive signal detection method based on a digital channelized receiver according to claim 3, wherein Specifically, S1 is as follows: S11: Determine the sub-channel bandwidth as f s / K and the processing bandwidth as 2f s / K according to the number of sub-channels K of uniform channelization and the AD sampling frequency f s / K; S12: Design a low-pass filter using the equiripple method and set the passband cut-off frequency of the filter to f s / 2K, the stopband starting frequency to f s / K, the passband ripple to 0.1 dB, and the stopband attenuation to 60 dB.

5. A method for interval adaptive signal detection based on a digital channelized receiver according to claim 1, wherein Specifically, the even and odd channels are processed as follows: the output of the even channel is multiplied by -1 every other clock cycle, and the output of the odd channel is delayed by one clock cycle.

6. The interval adaptive signal detection method based on a digital channelized receiver according to claim 1, wherein Specifically, S7 is as follows: S71: Set the detection threshold V T When using L adjacent channels as a detection interval, the channels within the same detection interval adopt the same detection threshold V Tl ; S72: Set register variables as n1, n2,..., n x , set n1 to 1 when the signal amplitude is greater than the threshold value, and set n1 to 0 when the signal amplitude is less than the threshold value; S73: Sequentially transfer the values of n1, n2,..., n x in a pipelined manner. When the logical AND result of all register variables is 1, the pulse is considered valid, and the pulse detection valid narg signal is pulled high; when the logical OR result of all register variables is 0, the pulse ends and the narg signal is reset to zero.

7. A method for interval adaptive signal detection based on a digital channelized receiver according to claim 1, characterized in that, Specifically, S8 is as follows: When the pulse is effective, perform multi-point phase difference frequency measurement on the signal, latch the frequency at the pulse front edge; count the pulse duration by the timer, calculate the pulse width, perform channel selection based on the frequency measurement result, output the pulse parameters, and form PDW for subsequent processing.

8. An interval adaptive signal detection system based on a digital channelized receiver, characterized in that, The system includes a storage device, and the storage device is used to execute the method described in claim 1.

9. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, and when the computer program is run by a processor, it executes a method for interval adaptive signal detection based on a digital channelized receiver described in any one of claims 1-7.

10. A computer device, characterized in that, The device includes a memory and a processor. A computer program is stored in the memory, and when the processor runs the computer program stored in the memory, the processor executes a method for interval adaptive signal detection based on a digital channelized receiver described in any one of claims 1-7.

Images