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CN-121984564-A - Blind detection method and system for uplink signal of low-orbit satellite

CN121984564ACN 121984564 ACN121984564 ACN 121984564ACN-121984564-A

Abstract

The invention particularly relates to a blind detection method and a blind detection system for an uplink signal of a low-orbit satellite, wherein the method comprises the steps of calculating a power spectrum of a received signal and equally dividing the power spectrum into M continuous sub-power spectrum segments; calculating the theoretical mean value and variance of the cepstrum zero entropy from the noise power and the number of power spectrum segments, calculating a threshold value threshold according to the mean value and variance and the set false alarm probability, and comparing the calculated information entropy with the threshold value threshold to realize the blind detection of the signal existence. The signal existence detection method provided by the invention based on the cepstrum energy non-uniform characteristic of the received signal power spectrum can effectively distinguish noise and signals without knowing any priori information in advance, and has lower calculation complexity.

Inventors

  • LIU MINGJIAN
  • YANG HUA
  • ZHANG JUNLIN

Assignees

  • 西安电子科技大学

Dates

Publication Date
20260505
Application Date
20260118

Claims (10)

  1. 1. A method for blind detection of a low-orbit satellite uplink signal, the method comprising: segmenting a received signal to obtain a plurality of equal-length signal segments; Calculating a power spectrum for each signal segment, and equally dividing the power spectrum into M continuous sub-power spectrum segments; Calculating a cepstrum zero point for each sub-power spectrum segment, constructing normalized discrete probability distribution based on the obtained M cepstrum zero points, and calculating shannon entropy as detection statistic; Estimating noise power from the received signal; Calculating theoretical mean and variance of cepstrum zero entropy under the assumption of pure noise based on the estimated noise power and the power spectrum segmentation number M, and calculating a detection threshold according to the preset false alarm probability; And step six, comparing the shannon entropy calculated in the step three with the threshold value threshold calculated in the step five, if the shannon entropy is larger than the threshold value threshold, judging the current signal section as noise, otherwise, judging the current signal section as an effective communication signal.
  2. 2. The method according to claim 1, wherein in the first step, the received signal x [ n ] is divided into Segment, each segment signal length bit N, the first segment signal is expressed as: 。
  3. 3. The method according to claim 2, wherein in the second step, the power spectrum is calculated for each sub-signal segment, and the power spectrum of the first sub-signal is expressed as: Wherein the method comprises the steps of The point number is the point number of the fast Fourier transform, the power spectrum is divided into M sections at equal intervals to obtain M sub-power spectrum sections, Can be divided by M, each sub-power spectrum segment comprises The m-th sub-power spectrum segment of the first sub-signal segment is expressed as: 。
  4. 4. The method according to claim 3, wherein in the third step, the log is obtained by taking the log of each sub-power spectrum segment of the first sub-signal segment The cepstrum zero value of the m th sub-power spectrum of the l sub-signal section is: Normalizing the calculated M sub-power spectrum cepstrum zero values to obtain a discrete probability function, wherein the probability of the mth cepstrum zero of the first sub-signal segment is as follows: Calculating normalized Information entropy of (2): 。
  5. 5. the method as set forth in claim 4, wherein in the fourth step, the noise variance is estimated by selecting a plurality of time periods with the lowest energy from the received signal x (n) 。
  6. 6. The method according to claim 5, wherein the theoretical mean and variance of the cepstrum zero-point entropy under the pure noise assumption is calculated in the fifth step by using the following formula: Wherein the method comprises the steps of Is an Euler constant; Modeling the probability distribution of the cepstrum zero entropy as: Order the Wherein Obeying a standard normal distribution with a mean value of 0 and a variance of 1, the normalized probability of each cepstrum zero point is expressed as: its shannon entropy is expressed as: And (3) making: the shannon entropy is written as: and (3) obtaining the average value of shannon entropy: solving variance of shannon entropy to obtain: Calculating theoretical mean and variance of cepstrum zero entropy by using mean and variance of cepstrum zero and combining power spectrum segmentation number M, and then combining false alarm probability The noise threshold is calculated, and the specific expression is as follows: Wherein the method comprises the steps of Is an upper-side quantile function of a standard normal distribution.
  7. 7. A low-orbit satellite uplink signal blind detection system, comprising: the signal segmentation module is used for segmenting the received signal to obtain a plurality of equal-length signal segments; the power spectrum analysis and segmentation module is used for calculating a power spectrum for each signal segment and equally dividing the power spectrum into M sub-power spectrum segments; The system comprises an entropy calculation module, a noise estimation module, a power generation module and a power generation module, wherein the entropy calculation module is used for calculating the cepstrum zero shannon entropy of a sub-power spectrum corresponding to each signal segment; the threshold calculation module is used for calculating theoretical statistics of cepstrum zero entropy based on noise power and the segmentation number M, and generating a detection threshold according to the false alarm probability; and the judging module is used for comparing the shannon entropy output by the entropy calculating module with the threshold output by the threshold calculating module to realize the blind detection of the existence of the signal.
  8. 8. A storage medium having stored thereon a computer program which, when executed by a processor, implements the low-earth satellite uplink signal blind detection method according to any one of claims 1 to 6.
  9. 9. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the low-earth satellite uplink signal blind detection method of any one of claims 1 to 6.
  10. 10. An electronic device, comprising: processor, and A memory for storing executable instructions of the processor; wherein the processor is configured to perform the low-orbit satellite uplink signal blind detection method of any one of claims 1 to 6 via execution of the executable instructions.

Description

Blind detection method and system for uplink signal of low-orbit satellite Technical Field The invention relates to the technical field of satellite communication and signal processing, in particular to a blind existence detection method for a ground terminal uplink signal in a low-orbit satellite communication system, and especially relates to a blind existence detection method for a low-orbit satellite uplink signal based on a segmented power spectrum cepstrum zero entropy characteristic and combined with a noise estimation self-adaptive detection threshold. Background In Low Earth Orbit (LEO) communication systems, ground terminals transmit signals to satellites moving at high speed via an uplink, and for purposes of spectrum supervision, electromagnetic environment detection or interference identification, non-cooperative receivers (e.g., radio monitoring stations, electronic reconnaissance platforms) often need to perform blind presence detection of these uplink signals without any cooperative information. Due to the low orbit height and the running speed block of the LEO satellite, the uplink has the characteristics of strong burstiness, large Doppler frequency offset, uncertain signal arrival time and the like, so that the traditional signal detection method faces serious challenges. At present, detection methods for signals in non-cooperative scenes mainly comprise energy detection, detection methods based on cyclostationary features and high-order statistical properties, and the like. However, these methods have significant limitations in the practical detection of LEO uplink signals. Firstly, although the traditional energy detection method does not need prior information, the calculation complexity is low, but the performance of the traditional energy detection method is seriously dependent on accurate noise power estimation, and in an LEO ground receiving scene, the traditional energy detection method is influenced by multipath effect, doppler frequency offset, atmospheric noise and thermal noise of a receiver together, so that the false alarm probability under a fixed threshold is difficult to control, and particularly, the detection probability is sharply reduced when the signal-to-noise ratio is lower than 0 dB. Secondly, some researches try to detect by using the structural features of modern waveforms, such as autocorrelation periodicity or complex cepstrum impulse caused by OFDM signal cyclic prefix, but such periodicity is significantly weakened under multipath rayleigh fading channel, resulting in poor robustness of such structure-dependent methods. Furthermore, although the detection method based on statistical characteristics, such as high-order accumulation, can theoretically suppress Gaussian noise, the detection method is essentially based on the assumption of high-order stability of signals, uplink signals are susceptible to multipath effects and Doppler frequency offset, so that the original statistical stability of signals is destroyed. In recent years, information entropy theory is introduced into non-cooperative detection, signals and noise are distinguished by quantifying the non-uniformity of energy distribution, but the existing power spectrum entropy detection utilizes each spectrum component to construct power spectrum entropy, and the local energy aggregation characteristic of LEO uplink signals in frequency domain entropy cannot be effectively captured. More importantly, the methods generally adopt an experience threshold, so that constant false alarm probability detection cannot be realized in a dynamic noise environment in order to establish a mapping relation between noise power and entropy statistics, and the requirements of actual supervision or reconnaissance tasks on reliability are difficult to meet. The method provided by the invention is a solution based on the above problems, does not depend on prior information of any signal, and has robustness to severe channel conditions such as multipath fading, low signal-to-noise ratio, large frequency offset and the like. The method can estimate the noise variance from the received data, and dynamically calculate the detection threshold based on a probability statistical model of the power spectrum cepstrum zero entropy under the assumption of pure noise and by combining with the preset false alarm probability. Meanwhile, the method has moderate calculation complexity and is more suitable for real-time operation on general monitoring equipment. It should be noted that the information disclosed in the above background section is only for enhancing understanding of the background of the invention and thus may include information that does not form the prior art that is already known to those of ordinary skill in the art. Disclosure of Invention Aiming at the problems that the traditional signal detection method depends on priori information, is sensitive to Doppler frequency offset and low signal to noise ratio and cannot