Single-bit signal detection method, device and system based on distributed array

Abstract

The invention discloses a single-bit signal detection method, device and system based on a distributed array, and belongs to the technical field of antennae, and the method comprises the steps: 1, building a distributed node single-bit signal receiving model; step 2, detecting a distributed single-bit signal, and in a fusion center, obtaining a single-bit detection statistic of the fusion center based on a Rao test criterion for detecting whether a target exists or not, and meanwhile, facilitating analysis of subsequent detection performance; 3, analyzing the single-bit signal detection performance, giving out single-bit detection statistic distribution, comparing the single-bit detection statistic distribution with the detection performance of the infinite-bit quantized signal, and compensating the single-bit detection performance; and 4, evaluating detection probabilities under different false alarm probabilities and signal-to-noise ratio conditions, and verifying a single-bit detection performance compensation scheme. According to the invention, data transmission quantity can be reduced while detection performance is ensured.

Description

Technical Field

[0001] The present invention relates to the field of antenna technology, and more specifically, to a single-bit signal detection method, device and system based on a distributed array. Background Art

[0002] Distributed array-based detection technology is often applied in a variety of fields, including ultra-long-range radar detection, deep space telemetry and remote control, and radio astronomy. Through efficient energy accumulation and large-scale apertures, it significantly improves long-range target detection and positioning, as well as electromagnetic interference suppression capabilities. However, the use of traditional high-precision analog-to-digital converters (ADCs) in large-scale array nodes inevitably faces problems such as high system cost and power consumption, as well as large data transmission volumes, which seriously hinder the practical application of distributed arrays. Therefore, considering the feasibility of using large-scale array nodes, it is necessary to perform low-precision quantization of the node received signal. One feasible approach is to use a single-bit ADC to quantize the signal at each node's receiving end. However, this efficient quantization method, which only retains the sign bit of the sampled data, cannot preserve the amplitude information in the high-precision quantized signal, which may result in a loss or even failure of the system's detection and positioning performance. Therefore, finding high-precision detection methods suitable for distributed single-bit quantized signals is crucial to reducing the data transmission volume of large-scale arrays. Summary of the Invention

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a single-bit signal detection method, device and system based on a distributed array, which can reduce the amount of data transmission while ensuring detection performance.

[0004] The object of the present invention is achieved through the following solutions:

[0005] A single-bit signal detection method based on a distributed array comprises the following steps:

[0006] Step 1: Establish a distributed node single-bit signal reception model;

[0007] Step 2: Detect distributed single-bit signals. At the fusion center, the single-bit detection statistic is obtained based on the Rao test criterion. This is used to detect the presence of the target and analyze subsequent detection performance.

[0008] Step 3: Analyze the single-bit signal detection performance, provide the single-bit detection statistic distribution, and compare it with the detection performance of the infinite-bit quantized signal to compensate for the single-bit detection performance;

[0009] Step 4: Evaluate the detection probability under different false alarm probabilities and signal-to-noise ratios and verify the single-bit detection performance compensation scheme.

[0010] Furthermore, in step 1, establishing a distributed node single-bit signal reception model specifically includes the following sub-steps:

[0011] L distributed nodes receive the signal r transmitted by the target p l (p), l = 1, ..., L, and after single-bit quantization according to the threshold zero, the single-bit quantized signal y l (p) Transmitted to the fusion center.

[0012] Furthermore, the L distributed nodes receive the signal r transmitted by the target p l (p), l = 1, ..., L, and single-bit quantization is performed according to the zero threshold, specifically including the following sub-steps:

[0013] Step 1-1: The expression of the high-precision quantized signal received by the distributed array of the lth node is:

[0014] r l (kT,p)=β l a(p)s(kT-τ(p)-t0)+w l (kT);

[0015] Among them, 1≤k≤N represents the number of samples, T represents the sampling interval, β l is the complex amplitude of the lth node, a(p) represents the array response, τ(p) and t0 represent the receiving delay of the lth node and the correlation between nodes at the time of signal transmission respectively; w l (kT) is the measurement noise of the lth node, which is assumed to obey zero mean and variance is Gaussian distribution;

[0016] Step 1-2: Write the N samples received by the lth node into a vector to obtain:

[0017]

[0018] in, represents the Kronecker product, w l Indicates noise;

[0019] Step 1-3: The node receives the signal r l (p) is compared with the zero threshold to obtain the single-bit quantized received signal:

[0020]

[0021] in, represents a single-bit quantizer, and sign(·) represents the sign function.

[0022] Furthermore, in step 2, the distributed single-bit signal is detected, and a single-bit detection statistic of the fusion center is obtained based on the Rao test criterion at the fusion center, which is used to detect the presence of the target and facilitate the analysis of subsequent detection performance. Specifically, the following sub-steps are included:

[0023] Step 2-1: Based on the single-bit quantized signal y l The target of (p) is a binary hypothesis problem:

[0024]

[0025] Among them, H0 indicates that the target does not exist, H1 indicates that the target exists, and M represents the number of nodes. The single-bit quantization is transmitted to the fusion center for further derivation of the detection criterion.

[0026] Step 2-2: Based on the Rao test criterion, the single-bit detection statistic of the fusion center is:

[0027] T R (p) = f T (β0)F -1 (β0)f(β0);

[0028] Where β0 represents the true value of the received signal amplitude under the assumption H0, that is, β0 = 0;

[0029] Step 2-3: Make Then we have:

[0030]

[0031] in, Indicates a single-bit received signal The probability density function under the assumption H1 is, represents the real part of the amplitude, represents the imaginary part of the amplitude, represents the derivation, Indicates the mean;

[0032] Step 2-4: The elements of f(β0) are obtained by the following formula:

[0033]

[0034] in,

[0035] The elements of F(β0) are obtained by the following formula:

[0036]

[0037] in, diag(·) represents a diagonal matrix;

[0038] Step 2-5: Substitute the expressions of f(β0) and F(β0) into T R (p) yields:

[0039]

[0040] in,

[0041] Furthermore, according to the detection threshold η0 known by the fusion center, the detection result of the target is obtained as follows:

[0042]

[0043] Among them, 0 means no target, and 1 means there is a target.

[0044] Furthermore, in step 3, analyzing the single-bit signal detection performance, providing a single-bit detection statistic distribution, and comparing it with the detection performance of an infinite-bit quantized signal to compensate for the single-bit detection performance specifically includes the following sub-steps:

[0045] Step 3-1: When the number of samples N is large enough, the single-bit detection statistic T of the fusion center R (p) approximately follows the following distribution:

[0046]

[0047] in, represents a chi-square distribution with noncentrality parameter λ and 2L degrees of freedom, represents the noncentral parameter, and its expression is:

[0048]

[0049] Step 3-2: The expression of the detection statistic of the high-precision quantization signal at the fusion center is:

[0050]

[0051] T G-∞ (p) approximately follows the following distribution:

[0052]

[0053] in, The expression is:

[0054]

[0055] Step 3-3: Compare the distribution of the detection statistics of single-bit and infinite-bit signals. When the false alarm probability is the same, the only difference in the detection performance between the two is the non-central parameter are different, and there are:

[0056]

[0057] The detection performance loss of single-bit signals compared to infinite-bit signals is π / 2; to address this issue, on the one hand, single-bit signals compensate for this performance loss by increasing the number of samples by π / 2 times, that is, to compensate for this performance loss; on the other hand, the number of distributed nodes is increased to compensate for this loss.

[0058] Further, after step 3-3, the following steps are also included:

[0059] Step 3-4: Let the number of nodes used when the detection probabilities of single-bit and infinite-bit signals are equal be L1 and L2 respectively, where L2 < L1, and the false alarm probability is P FA , then the expressions for the detection thresholds of the two are:

[0060]

[0061] Correspondingly, the expressions for the detection probabilities of the two are:

[0062]

[0063] where represents the complementary function of the cumulative distribution function of the chi-square distribution;

[0064] Step 3-5: Since the detection probabilities of single-bit and infinite-bit signals are equal, there is:

[0065]

[0066] Solve for L1 and L2 that satisfy the conditions through numerical solution methods.

[0067] A single-bit signal detection device based on a distributed array, comprising:

[0068] A model construction module for establishing a single-bit signal reception model for distributed nodes;

[0069] A detection module for detecting distributed single-bit signals. At the fusion center, a single-bit detection statistic at the fusion center is obtained based on the Rao test criterion, which is used to detect the presence or absence of a target and analyze the subsequent detection performance;

[0070] A detection performance analysis and comparison module for analyzing the detection performance of single-bit signals, giving the distribution of single-bit detection statistics, and comparing its detection performance with that of infinite-bit quantization signals to compensate for the single-bit detection performance;

[0071] The detection performance evaluation module is used to evaluate the detection probability under different false alarm probabilities and signal-to-noise ratio conditions and to verify the single-bit detection performance compensation scheme.

[0072] A single-bit signal detection system based on a distributed array includes the single-bit signal detection device based on a distributed array as described above.

[0073] The beneficial effects of the present invention include:

[0074] (1) Efficient data transmission method. The present invention provides a single-bit signal detection method based on a distributed array. By performing single-bit quantization on the received signal at the receiving end of the node, compared with the traditional high-precision quantization method, the single-bit quantization method greatly reduces the data transmission volume, hardware power consumption and system cost.

[0075] (2) Distributed single-bit detection method. The present invention provides a detection method suitable for distributed single-bit quantized signals. Based on the Rao test criterion, the single-bit detection statistic of the fusion center is given. The proposed method does not require the estimation of the complex amplitude of the received signal at different nodes, which greatly reduces the computational complexity of the system.

[0076] (3) Compensation scheme for single-bit signal detection performance. The present invention provides a single-bit signal detection method based on a distributed array. By comparing the detection performance difference between a single-bit signal and an infinite-bit quantized signal, it is proposed that the detection performance loss of a single-bit signal can be compensated by increasing the number of samples or the number of nodes, thereby reducing the data transmission volume while maintaining the detection performance of the single-bit signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0078] Figure 1 A flowchart of the steps of the method according to an embodiment of the present invention;

[0079] Figure 2 It is the geometric distribution diagram of each node position and target position;

[0080] Figure 3 The time-frequency diagram of the high-precision quantized signal received by a single node;

[0081] Figure 4 The graphs showing the variation of detection probability with false alarm probability for single-bit detection method and infinite-bit detection method are shown below;

[0082] Figure 5 The relationship diagram of the number of nodes used when the detection probability of single-bit and infinite-bit signals is equal;

[0083] Figure 6 The graphs showing the variation of detection probability with the number of nodes for the single-bit detection method and the infinite-bit detection method;

[0084] Figure 7 The graph shows the variation of detection probability with signal-to-noise ratio for single-bit detection method and infinite-bit detection method. DETAILED DESCRIPTION

[0085] All features disclosed in all embodiments in this specification, or steps in all methods or processes implicitly disclosed, except for mutually exclusive features and / or steps, can be combined and / or expanded or replaced in any manner.

[0086] The specific implementation process of the present invention is as follows:

[0087] As a first aspect of the present invention, a single-bit signal detection method based on a distributed array is specifically provided, comprising the following steps:

[0088] Step 1: Establish a distributed node single-bit signal receiving model, L distributed nodes ( Figure 1 ) receives the signal r transmitted by the target p l (p)(l=1,…,L), and after single-bit quantization according to threshold 0, the single-bit quantized signal y l (p) transmitted to a fusion center;

[0089] Step 2: Establish a distributed single-bit signal detection method. At the fusion center, the single-bit detection statistic is obtained based on the Rao test criterion. This is used to detect the presence of the target and facilitate subsequent analysis of detection performance.

[0090] Step 3: Develop a single-bit signal detection performance analysis, present the distribution of the single-bit detection statistic, compare it with the detection performance of an infinite-bit quantized signal, and present a method to compensate for the single-bit detection performance.

[0091] Step 4: Establish a detection performance evaluation module to evaluate the detection probability of the proposed method under different false alarm probabilities and signal-to-noise ratio conditions, and verify the single-bit detection performance compensation scheme.

[0092] In a further optional implementation manner, step 1 of establishing a distributed node single-bit signal reception model specifically includes the following sub-steps:

[0093] Step 1-1: The expression of the high-precision (infinite bit) quantized signal received by the lth (l=1,…,L) node distributed array is:

[0094] r l (kT,p)=β l a(p)s(kT-τ(p)-t0)+w l (kT);

[0095] Among them, 1≤k≤N represents the number of samples, T represents the sampling interval, β l is the complex amplitude of the lth node, a(p) represents the array response, τ(p) and t0 represent the receiving delay of the lth node and the correlation between nodes at the time of signal transmission respectively; w l (kT) is the measurement noise of the lth node, assuming it obeys zero mean and variance is Gaussian distribution.

[0096] Step 1-2: Write the N samples received by the lth node into a vector to get:

[0097]

[0098] in,

[0099] Step 1-3: The node receives the signal r l (p) is compared with the zero threshold to obtain the single-bit received signal:

[0100]

[0101] in, represents a single-bit quantizer, and sign(·) represents the sign function.

[0102] More specifically, see Figure 2 , gives a geometric distribution diagram of the target location at (875,634) m, with 50 receiving nodes randomly distributed in a rectangular range of 10 m × 500 m, and each node consists of a single antenna; see Figure 3 , gives the high-precision quantized signal r received by a single node l (p)(l=1,…,L), the sampling frequency of the target transmission signal is 10MHz, the duration is 20μs, the bandwidth of the signal flat spectrum is 5MHz, and the single-bit signal y is obtained after quantization according to the zero threshold. l (p), which is transmitted to the fusion center for further object detection.

[0103] In a further optional embodiment, step 2 specifically includes the following steps:

[0104] Step 2-1: Based on the single-bit quantized signal y l The target of (p) is a binary hypothesis problem:

[0105]

[0106] Where H0 indicates that the target does not exist, and H1 indicates that the target exists. The single-bit quantization is transmitted to the fusion center for further derivation of detection criteria.

[0107] Step 2-2: Based on the Rao test criterion, the single-bit detection statistic of the fusion center is:

[0108] T R (p) = f T (β0)F -1 (β0)f(β0);

[0109] Wherein, β0 represents the true value of the received signal amplitude under the assumption H0, that is, β0=0.

[0110] Step 2-3: Make Then we have:

[0111]

[0112] in, Indicates a single-bit received signal Probability density function under hypothesis H1.

[0113] Step 2-4: The elements of f(β0) can be obtained by the following formula:

[0114]

[0115] in,

[0116] The elements of F(β0) can be obtained by the following formula:

[0117]

[0118] in, diag(·) represents a diagonal matrix.

[0119] Step 2-5: Substitute the expressions of f(β0) and F(β0) into T R (p) can be obtained

[0120]

[0121] in,

[0122] Among them, according to the detection threshold η0 known by the fusion center, the detection result of the target is obtained as follows:

[0123]

[0124] Among them, 0 indicates no target, and 1 indicates there is a target.

[0125] In a further optional implementation manner, step 3 specifically includes the following steps:

[0126] Step 3-1: When the number of samples N is large enough, the single-bit detection statistic T of the fusion center R (p) approximately follows the following distribution:

[0127]

[0128] Among them, represents a chi-square distribution with a non-central parameter of λ and a degree of freedom of 2L, represents the non-central parameter, and its expression is:

[0129]

[0130] Step 3-2: Similarly, the expression of the detection statistic of the high-precision quantization signal (infinite bits) of the fusion center can be obtained as:

[0131]

[0132] T G-∞ (p) approximately follows the following distribution:

[0133]

[0134] Among them, The expression of

[0135]

[0136] By comparing the distributions of the detection statistics of the single-bit and infinite-bit signals, it can be seen that when the false alarm probability is the same, the only difference in their detection performance lies in the non-central parameter is different, and there is:

[0137]

[0138] Therefore, the detection performance loss of the single-bit signal compared to the infinite-bit signal is π / 2. To address this problem, on the one hand, the single-bit signal can compensate for this performance loss by increasing the number of samples by π / 2 times so that On the other hand, the number of distributed nodes can also be increased to compensate for this loss.

[0139] Step 3-4: Assume that the number of nodes adopted when the detection probabilities of the single-bit and infinite-bit signals are equal are L1 and L2 (L2 < L1), and the false alarm probability is P FA , then the expressions of their detection thresholds are respectively:

[0140]

[0141] Correspondingly, the expressions of the detection probabilities of the two are:

[0142]

[0143] in, Represents the complement of the chi-squared cumulative distribution function.

[0144] For more details, see Figure 5 , the variation of detection probability with false alarm probability for single-bit detection method and infinite-bit detection method is given. In order to obtain the detection probability, the number of Monte Carlo experiments is set to 10 6 ,When the signal to noise ratio is -20dB, the number of nodes is 16, and the number of samples is 100, it can be seen that the ,theoretical results of the detection probability curves of the two algorithms are consistent ,with the Monte Carlo experimental results, and that the detection performance of ,single-bit signals suffers from loss, especially at low false alarm probabilities.

[0145] Step 3-5: Since the detection probabilities of single-bit and infinite-bit signals are equal, we have:

[0146]

[0147] L1 and L2 that meet the conditions can be solved by numerical solution method.

[0148] For more details, see Figure 4 , gives the relationship between the number of nodes used when the detection probability of single-bit and infinite-bit signals is equal. Using the golden section numerical solution method, the curves of the number of nodes used to achieve the same detection performance when the signal-to-noise ratio is -22dB and the number of samples is 100, 100, and 30, respectively, show that when the number of nodes or samples is small, the ratio of the number of nodes used by the two methods will change slightly; as the number of nodes or samples increases, the ratio is basically fixed at around 2.5. In other words, by increasing the number of nodes by 1.5 times, the single-bit signal can compensate for the detection performance loss caused by single-bit quantization and achieve the same detection probability as the infinite-bit quantized signal.

[0149] In a further optional implementation, step 4 specifically includes: evaluating the detection probability of the proposed method under different false alarm probabilities and signal-to-noise ratio conditions, and verifying the single-bit detection performance compensation scheme.

[0150] In a more specific embodiment, a detection performance evaluation module is established, which specifically includes the following steps:

[0151] See Figure 6, the variation of detection probability of single-bit detection method and infinite-bit detection method with the number of nodes is given.

[0152] It can be seen that when O=100 and O=30, by increasing the number of nodes by about 1.5 times for compensation, the detection probability curve of the single-bit signal basically coincides with the detection probability of the infinite-bit quantized signal.

[0153] For more details, see Figure 7 , shows how the detection probabilities of the single-bit and infinite-bit detection methods vary with the signal-to-noise ratio. As can be seen from the figure, the single-bit detection method achieves a detection probability that is almost identical to that of the infinite-bit detection method by increasing the number of samples by 0.57 times or the number of nodes by 1.5 times. This loss decreases as the signal-to-noise ratio increases, and ultimately, the detection probabilities of both methods approach 1.

[0154] As a second aspect of the present invention, based on the above method, a single-bit signal detection device based on a distributed array is provided, comprising:

[0155] A model building module, used to establish a distributed node single-bit signal reception model;

[0156] The detection module is used to detect distributed single-bit signals. At the fusion center, the single-bit detection statistic of the fusion center is obtained based on the Rao test criterion. This is used to detect the presence of the target and analyze the subsequent detection performance.

[0157] Detection performance analysis and comparison module, used to analyze the detection performance of single-bit signals, provide the single-bit detection statistic distribution, and compare it with the detection performance of infinite-bit quantized signals to compensate for the single-bit detection performance;

[0158] The detection performance evaluation module is used to evaluate the detection probability under different false alarm probabilities and signal-to-noise ratio conditions and to verify the single-bit detection performance compensation scheme.

[0159] As a third aspect of the present invention, based on the above method, a single-bit signal detection system based on a distributed array is provided, comprising the single-bit signal detection device based on a distributed array as described above.

[0160] The specific implementation of the present invention is not limited to the above-mentioned methods. The above description is only the preferred embodiment of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein. It is obvious that various changes, adjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments. Without departing from the principles and concepts of the present invention, it can also include more other equivalent embodiments, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A single-bit signal detection method based on a distributed array, characterized in that: The following steps are involved: Step 1: Establish a distributed node single-bit signal reception model; Step 2: Detect distributed single-bit signals. At the fusion center, the single-bit detection statistic is obtained based on the Rao test criterion. This is used to detect the presence of the target and analyze subsequent detection performance. Step 3: Analyze the single-bit signal detection performance, provide the single-bit detection statistic distribution, and compare it with the detection performance of the infinite-bit quantized signal to compensate for the single-bit detection performance; Step 4: Evaluate the detection probability under different false alarm probabilities and signal-to-noise ratios and verify the single-bit detection performance compensation scheme.

2. The single-bit signal detection method based on a distributed array according to claim 1, characterized in that: In step 1, establishing a distributed node single-bit signal reception model specifically includes the following sub-steps: L distributed nodes receive the signal r transmitted by the target p l (p), l = 1, ..., L, and after single-bit quantization according to the threshold zero, the single-bit quantized signal y l (p) Transmitted to the fusion center.

3. The single-bit signal detection method based on a distributed array according to claim 2, characterized in that: The L distributed nodes receive the signal r transmitted by the target p l (p), l = 1, ..., L, and single-bit quantization is performed according to the zero threshold, specifically including the following sub-steps: Step 1-1: The expression of the high-precision quantized signal received by the distributed array of the lth node is: r l (kT,p)=β l a(p)s(kT-τ(p)-t0)+w l (kT); Among them, 1≤k≤N represents the number of samples, T represents the sampling interval, β l is the complex amplitude of the lth node, a(p) represents the array response, τ(p) and t0 represent the receiving delay of the lth node and the correlation between nodes at the time of signal transmission respectively; w l (kT) is the measurement noise of the lth node, which is assumed to obey zero mean and variance is Gaussian distribution; Step 1-2: Write the N samples received by the lth node into a vector to obtain: in, represents the Kronecker product, w l Indicates noise; Step 1-3: The node receives the signal r l (p) is compared with the zero threshold to obtain the single-bit quantized received signal: in, represents a single-bit quantizer, and sign(·) represents the sign function.

4. The single-bit signal detection method based on a distributed array according to claim 3, characterized in that: In step 2, the distributed single-bit signal is detected, and a single-bit detection statistic of the fusion center is obtained based on the Rao test criterion at the fusion center. This is used to detect the presence of the target and facilitate analysis of subsequent detection performance. The specific sub-steps include the following: Step 2-1: Based on the single-bit quantized signal y l The target of (p) is a binary hypothesis problem: Among them, H0 indicates that the target does not exist, H1 indicates that the target exists, and M represents the number of nodes. The single-bit quantization is transmitted to the fusion center for further derivation of the detection criterion. Step 2-2: Based on the Rao test criterion, the single-bit detection statistic of the fusion center is: T R (p)=f T (β0)F -1 (β0)f(β0); Where β0 represents the true value of the received signal amplitude under the assumption H0, that is, β0 = 0; Step 2-3: Make Then we have: in, Indicates a single-bit received signal The probability density function under the assumption H1 is, represents the real part of the amplitude, represents the imaginary part of the amplitude, represents the derivation, Indicates the mean; Step 2-4: The elements of f(β0) are obtained by the following formula: in, The elements of F(β0) are obtained by the following formula: in, diag(·) represents a diagonal matrix; Step 2-5: Substitute the expressions of f(β0) and F(β0) into T R (p) yields: in, 5. The single-bit signal detection method based on a distributed array according to claim 4, characterized in that: According to the detection threshold η0 known by the fusion center, the detection result of the target is: Among them, 0 means no target, and 1 means there is a target.

6. The single-bit signal detection method based on a distributed array according to claim 4, characterized in that: In step 3, the single-bit signal detection performance is analyzed, a single-bit detection statistic distribution is given, and the distribution is compared with the detection performance of an infinite-bit quantized signal to compensate for the single-bit detection performance. Specifically, the following sub-steps are included: Step 3-1: When the number of samples N is large enough, the single-bit detection statistic T of the fusion center R (p) approximately follows the following distribution: in, represents a chi-square distribution with noncentrality parameter λ and 2L degrees of freedom, represents the noncentral parameter, and its expression is: Step 3-2: The expression of the detection statistic of the high-precision quantization signal at the fusion center is: T G-∞ (p) approximately follows the following distribution: in, The expression is: Step 3-3: Compare the distribution of the detection statistics of single-bit and infinite-bit signals. When the false alarm probability is the same, the only difference in the detection performance between the two is the non-central parameter Different, and have: The detection performance loss of a single-bit signal compared to an infinite-bit signal is π / 2. To address this problem, on the one hand, the single-bit signal can be obtained by increasing the number of samples by π / 2. This compensates for the performance loss; on the other hand, the number of distributed nodes is increased to compensate for the loss.

7. The single-bit signal detection method based on a distributed array according to claim 6, characterized in that: After step 3-3, the following steps are also included: Step 3-4: Let the number of nodes adopted when the detection probabilities of single-bit and infinite-bit signals are equal be L1 and L2 respectively, where L2 < L1, and the false alarm probability is P FA , then the expressions for the detection thresholds of the two are as follows: Correspondingly, the expressions of the detection probabilities of the two are: in, The complement of the cumulative distribution function representing the chi-square distribution; Step 3-5: Since the detection probabilities of single-bit and infinite-bit signals are equal, we have: The L1 and L2 that meet the conditions are solved by numerical solution method.

8. A single-bit signal detection device based on a distributed array, characterized in that: include: A model building module, used to establish a distributed node single-bit signal reception model; The detection module is used to detect distributed single-bit signals. At the fusion center, the single-bit detection statistic of the fusion center is obtained based on the Rao test criterion. This is used to detect the presence of the target and analyze the subsequent detection performance. Detection performance analysis and comparison module, used to analyze the detection performance of single-bit signals, provide the single-bit detection statistic distribution, and compare it with the detection performance of infinite-bit quantized signals to compensate for the single-bit detection performance; The detection performance evaluation module is used to evaluate the detection probability under different false alarm probabilities and signal-to-noise ratio conditions and to verify the single-bit detection performance compensation scheme.

9. A single-bit signal detection system based on a distributed array, characterized in that: It includes the single-bit signal detection device based on a distributed array as described in claim 8.

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