Time hopping code estimation and multi-hop coherent combination method and device for satellite communication

Abstract

The invention discloses a time hopping code estimation and multi-hop coherent combination method and device for satellite communication, and belongs to the field of digital signal processing. A sending end disperses information symbols in specified time slots of different time frames for repeated transmission, the time slot where a sending signal is located is determined by a time hopping code, and both communication parties agree that the time hopping code changes randomly within a predetermined range. And a receiving end performs time hopping code and carrier phase joint estimation on the time hopping signal transmitted through the AWGN channel by using a cross entropy iteration method. Performing binary quantization on a time hopping code and a carrier phase, obtaining an estimated value of the time hopping code and the carrier phase according to a binary quantization bit generation probability, selecting a time slot where a signal is located and compensating the carrier phase, performing coherent combination on multi-hop signals, and selecting a sample with small combined signal-to-noise ratio loss to update the binary quantization bit generation probability. And iterating to obtain a global optimal vector group. According to the global optimal vector group, multi-hop coherent combination is realized, the demodulation signal-to-noise ratio is improved, and the reliability of time-hopping communication is effectively improved with low complexity.

Description

Technical Field

[0001] The invention relates to a cross-entropy iteration-assisted time-hopping code estimation and multi-hop coherent combining method and device, and belongs to the field of digital signal processing. Background Art

[0002] In the field of satellite communications, the broadcast characteristics of wireless signals make the signals at risk of being intercepted, thus posing a serious threat to information security. Starting from the idea of ​​suppressing and eliminating the detectable and attackable features in the communication signal, a random process is introduced to randomize the signal transmission time. In the time-hopping communication system, the signal is sent in the time segment of the hopping, which destroys the continuity of the signal in the time domain during the communication process and increases the difficulty of intercepting the signal. For the satellite-to-ground uplink, in addition to requiring the information content not to be detected, it is also required that the signal itself not be detected, otherwise the non-cooperative party can find the terminal location by detecting the existence of the uplink signal and attack the terminal. In order to improve the communication concealment of the satellite-to-ground uplink, the transmitter further reduces the signal power, disperses the information symbols to be sent in different time slots of multiple time frames for repeated transmission, and uses a randomly changing time-hopping code to control the movement of the signal in time each time it is sent, which creates an extremely low signal-to-noise ratio condition for the uplink and increases the uncertainty of time. In order to recover the information symbol, the receiver needs to merge the multi-hop signals with extremely low signal-to-noise ratio conditions dispersed in different time slots of each time frame to obtain a signal-to-noise ratio gain. Since the carrier phase of each frame signal is random to the receiving end, in order to reduce the loss of the combined signal-to-noise ratio, the receiving end is required to accurately estimate and compensate for the carrier phase of each frame signal. In addition, due to the randomness of the time-hopping code, it is necessary to search for the time-hopping code of each time frame to finally complete the coherent merging and demodulation of the multi-hop signal. The above problem is the estimation problem of the multi-dimensional parameters of the multi-hop carrier phase and the time-hopping code under extremely low signal-to-noise ratio conditions. From the perspective of maximum likelihood estimation, this problem is a multi-dimensional nonlinear optimization problem, which is very difficult to solve directly. The traditional traversal method has high complexity.

[0003] As a global random optimization algorithm, cross entropy is widely used in multi-dimensional, large-scale, and nonlinear optimization problems. The optimization problem is converted into a probability estimation problem of a low-probability event, that is, the occurrence of the optimal solution is a low-probability event. An adaptive key sampling strategy is adopted to select samples with better effects according to the objective function to update the probability distribution, and new samples are generated using the updated probability distribution. The optimal solution is more likely to occur through iteration. Applying cross entropy to the joint estimation of multi-hop carrier phase and time-hopping code can reduce the complexity of parameter estimation. Based on this, a cross-entropy iteration-assisted time-hopping code estimation and multi-hop coherent merging method is proposed. Summary of the invention

[0004] In view of the problem of loss of combined signal-to-noise ratio caused by the estimation deviation of time-hopping code and carrier phase in the time-hopping communication system, the purpose of the present invention is to provide a time-hopping code estimation and multi-hop coherent combining method and device assisted by cross-entropy iteration, which performs parallel joint estimation of multi-hop carrier phase and time-hopping code through random search, and makes the estimation parameters converge to the joint estimation optimal solution during the iteration process. The time-hopping code and multi-hop carrier phase are synchronized according to the joint estimation optimal solution, and then the coherent combining of multi-hop signals is realized. The demodulation signal-to-noise ratio can be improved through coherent combining with lower complexity, and the reliability of time-hopping communication can be effectively improved.

[0005] The objective of the present invention is achieved through the following technical solutions:

[0006] The invention discloses a method for satellite communication-oriented time-hopping code estimation and multi-hop coherent merging. The transmitting end disperses information symbols in designated time slots of different time frames for repeated transmission. The time slot where the signal is sent is determined by the time-hopping code. The communicating parties agree that the time-hopping code changes randomly within a predetermined range. The receiving end uses the cross-entropy iteration method to jointly estimate the time-hopping code and the carrier phase of the time-hopping signal transmitted through the AWGN channel. The time-hopping code and the carrier phase are binary quantized, and the estimated values ​​of the time-hopping code and the carrier phase are obtained from the binary quantization bit generation probability. The time slot where the signal is located is selected and the carrier phase is compensated. The multi-hop signals are coherently merged, and samples with a smaller loss of the combined signal-to-noise ratio are selected to update the binary quantization bit generation probability, and the global optimal vector group is obtained by iterating in sequence. According to the global optimal vector group, multi-hop coherent merging is realized to improve the demodulation signal-to-noise ratio, and the reliability of time-hopping communication is effectively improved with low complexity.

[0007] The invention discloses a method for satellite communication-oriented time hopping code estimation and multi-hop coherent combining, comprising the following steps:

[0008] Step 1: Divide the communication time window into multiple time frames, each of which includes multiple time slots. The information symbols to be sent are modulated by BPSK and then repeatedly transmitted in the specified time slots of multiple time frames. The time slot position of the signal sent in each time frame is determined by the time-hopping code corresponding to the frame. The communicating parties agree that the time-hopping code changes randomly within a predetermined range to generate a BPSK-modulated time-hopping signal with a random time-hopping code.

[0009] The BPSK modulated time-hopping signal with random time-hopping code is generated as shown below:

[0010]

[0011] N to be sent s Symbols in N f The transmission is repeated in time frames, and the duration of a single time frame is T f , b k represents the kth BPSK modulation symbol, b k∈{-1,+1}, w(t) represents a single pulse waveform, c m represents the time-hopping code of the mth time frame, c m ∈{0,1,...,N h -1}, time-hopping code c m Add a time shift c to the signal of the mth time frame m T c , N h T c =T f , T s is the duration of a single symbol, T c =N s T s , f0 is the carrier frequency of the transmitted signal, φ 0,m It is the initial phase of the transmitted signal carrier in the mth time frame.

[0012] Step 2: Send the BPSK modulated time-hopping signal obtained in step 1 into the AWGN channel, and receive the signal transmitted through the AWGN channel.

[0013] The received signal after passing through the AWGN channel is expressed as

[0014]

[0015] Where A is the amplitude of the transmitted signal when it reaches the receiver, τ is the delay of the receiving end relative to the transmitting end, and f d is the frequency deviation of the received signal relative to the transmitted signal, φ m is the initial phase of the carrier of the received signal in the mth time frame, n(t) represents additive complex Gaussian white noise, with a mean of 0 and a variance of Receiver delay τ and frequency offset f d Ideally synchronized.

[0016] Step 3: The initial phase search range of the carrier of each frame of the received signal is [0,2π). The two parties agree on c m The search range is {0,1,…,N h -1}, the initial phase of the carrier of the received signal of the mth frame and the time-hopping code search parameters are in A mapping relationship is established between the search value and the binary code. D1 and D2 are binary quantization bit numbers. Each carrier phase search value corresponds to a D1bit binary number, and each time hopping code search value corresponds to a D2bit binary number, thereby realizing parameter quantization of the time hopping code and the carrier phase of each hopping signal.

[0017] φ m,d represents the initial phase estimate of the dth carrier of the mth frame, d∈{1,2,...,N1}, and

[0018]

[0019] Represent d-1 as a binary number of D1 bits, and then establish φ from the above formula m,d The mapping relationship with the D1bit binary number.

[0020] c m,u represents the u-th time hopping code estimate of the m-th frame, u∈{1, 2, ..., N2}, and N2=N h ,have

[0021] c m,u =u-1 (4)

[0022] Represent u-1 as a D2-bit binary number, and then establish c from the above formula m,u The mapping relationship with D2bit binary number.

[0023] Step 4: Initialize the binary quantization bit generation probability as the input of the first cross entropy iteration, and obtain N according to the binary quantization bit generation probability c The binary code of each group is called a candidate group. The time hopping code estimation value and the carrier phase estimation value are obtained by binary code mapping. The time slot where the signal is located is selected according to the time hopping code estimation value. The signal carrier phase of the selected time slot is compensated according to the carrier phase estimation value, and the compensated multi-hop signals are coherently combined. The signal-to-noise ratio of the combined signal is estimated, and the difference between the estimated signal-to-noise ratio and the theoretical signal-to-noise ratio is calculated to obtain the combined signal-to-noise ratio loss. The combined signal-to-noise ratio loss is used as the objective function of the cross entropy iteration.

[0024] N f The total number of binary quantization bits of the frame hopping code and the carrier phase estimation value is N f (D1+D2)bit, the probability of generating binary quantization bits in the i-th cross entropy iteration is in represents the probability that the jth quantization bit takes 1, given by The resulting binary quantization bits are represented as in represents the jth quantization bit, b i The mapped time hopping code and carrier phase estimation value are recorded as Initialize the binary quantization bit generation probability to in Indicates size is 1×N f(D1+D2), a vector whose elements are all 1, generates a binary code according to the probability, obtains the time-hopping code and the carrier phase estimation value, selects the time slot where the signal is located according to the time-hopping code estimation value, compensates the signal carrier phase of the selected time slot according to the carrier phase estimation value, and coherently combines the compensated multi-hop signals.

[0025] The time shift in the mth frame is v m T c The kth data in a time slot is expressed as

[0026]

[0027] Among them C m (v m ) is the time-hopping code indicator function

[0028]

[0029] Estimated value based on time-hopping code Select the time slot position where the mth frame signal is located, and calculate the carrier phase estimate value Compensate the carrier phase of the selected time slot in the mth frame, N f The signal after the kth data of the selected time slot of the time frame is combined is expressed as

[0030]

[0031] Let γ1 represent the single-hop signal-to-noise ratio, then the theoretical signal-to-noise ratio after merging is

[0032] γ comb =γ1+10log 10 (N f ) (8)

[0033] The difference between the estimated signal-to-noise ratio and the theoretical signal-to-noise ratio is calculated according to the following formula, and the combined signal-to-noise ratio loss is obtained as follows:

[0034]

[0035] in, In order to actually combine the estimated results of the signal-to-noise ratio, the signal-to-noise ratio estimation method used is:

[0036]

[0037] Among them, mean() means taking the mean, and var() means taking the variance.

[0038] The estimated results of the combined theoretical signal-to-noise ratio and the actual combined signal-to-noise ratio are substituted into the combined signal-to-noise ratio loss formula to calculate the combined signal-to-noise ratio loss. The calculated combined signal-to-noise ratio loss is used as the objective function of the cross entropy iteration. c Group parameters to get Nc The combined signal-to-noise ratio loss estimation results.

[0039] Step 5: Use cross entropy to iteratively update the parameter estimation results and replace the N obtained in step 4 c Sort the combined signal-to-noise ratio losses from small to large, and select the top N with the smallest combined signal-to-noise ratio loss e The time hopping code and carrier phase quantization parameters corresponding to the group are taken as the preferred group, and the probability of each bit in the binary quantization bits of the preferred group taking 0 or 1 is calculated. According to the probability obtained by statistics of the preferred group, the probability of binary quantization bit generation for the next cross entropy iteration is obtained.

[0040] N c The combined signal-to-noise ratio loss estimation results are sorted from small to large, and the combined signal-to-noise ratio loss sorting result obtained by the i-th cross entropy iteration is recorded as The corresponding time hopping code and carrier phase binary quantization bits are recorded as Depend on The estimated value obtained by mapping is recorded as l∈{1, 2, ..., N c}. Take the top N with the smallest combined signal-to-noise ratio loss e Group binary quantization bits into preferred groups The corresponding time hopping code and carrier phase estimation value are Calculate the probability p of each quantized bit in the preferred group being 1 i+1

[0041]

[0042] P i+1 Perform smoothing and update the generation probability of the next iteration

[0043]

[0044] Among them, α is the smoothing coefficient, α∈(0,1], the larger α is, the faster the convergence speed is.

[0045] Step 6: By setting the global optimal vector group to avoid falling into the local optimal solution, the time hopping code and carrier phase estimation value with the smallest signal-to-noise ratio loss in the cross entropy iteration process are selected as the global optimal vector group. When each element in becomes 0 or 1, or when the number of iterations reaches the set maximum number of iterations, the cross entropy iteration stops and the global optimal vector group is output. The time slot selection and carrier phase compensation of the received signal are performed according to the global optimal vector group obtained by random search, and the demodulation signal-to-noise ratio is improved through multi-hop coherent combining, which effectively improves the reliability of time-hopping communication with low complexity.

[0046] set up Used to record the minimum combined signal-to-noise ratio loss from the 1st iteration to the i-th iteration, set As a record The corresponding time hopping code and carrier phase estimation value, when the N obtained in the i-th iteration in step 5 c The minimum value of the combined signal-to-noise ratio loss satisfies When Update the value to and Update the value to otherwise and No change. Calculation The number of elements in is 0 or 1, when M<N f (D1+D2) and the current number of iterations is less than the set maximum number of iterations, As the input condition for the next cross entropy iteration, repeat steps 4 to 6. f (D1+D2) or when the current number of iterations is equal to the set maximum number of iterations, the cross entropy iteration stops and the global optimal vector group is output.

[0047] According to the time-hopping code and carrier phase estimation values ​​in the global optimal vector group obtained by the above random search process, time slot selection and carrier phase compensation are performed on the received signal, and the compensated multi-hop signals are coherently combined to improve the demodulation signal-to-noise ratio, thereby effectively improving communication reliability with low complexity.

[0048] The invention also discloses a satellite communication-oriented time hopping code estimation and multi-hop coherent combining device, which is used to implement a satellite communication-oriented time hopping code estimation and multi-hop coherent combining method. The satellite communication-oriented time hopping code estimation and multi-hop coherent combining device comprises a parameter quantization unit, a parameter compensation and multi-hop combining unit, a signal-to-noise ratio estimation unit, and a cross entropy iteration unit.

[0049] The parameter quantization unit is used to establish a mapping relationship between the time hopping code and carrier phase search value and the binary quantization bit.

[0050] The parameter compensation and multi-hop merging unit performs parameter compensation and multi-hop merging based on the estimation result obtained by the cross entropy iteration unit, selects the time slot where the signal is located according to the time hopping code estimation value, compensates the carrier phase of the selected time slot signal according to the carrier phase estimation value, and coherently combines the compensated multi-hop signals.

[0051] The signal-to-noise ratio estimation unit estimates the signal-to-noise ratio of the combined signal obtained by the parameter compensation and combining unit, calculates the difference between the estimated signal-to-noise ratio and the theoretical signal-to-noise ratio, and obtains the combined signal-to-noise ratio loss.

[0052] The cross entropy iteration unit generates a binary code from a binary quantization bit generation probability, generates a time hopping code and a carrier phase estimation value according to the binary code and a mapping relationship obtained by the parameter quantization unit, outputs the estimation value to the parameter compensation and multi-hop merging unit, takes the combined signal-to-noise ratio loss calculated by the signal-to-noise ratio estimation unit as an objective function, selects samples with a smaller combined signal-to-noise ratio loss as a preferred group, regenerates the binary quantization bit generation probability for the next iteration according to the preferred group, records the time hopping code and the carrier phase estimation value corresponding to the minimum combined signal-to-noise ratio loss as a global optimal vector group during the iteration process, and outputs the global optimal vector group after the iteration stops.

[0053] Beneficial effects:

[0054] 1. The cross-entropy iteration-assisted time-hopping code estimation and coherent merging method and device disclosed in the present invention adopt an adaptive key sampling strategy, with minimizing the combined signal-to-noise ratio loss as the objective function, and converge to the optimal solution through rapid iteration through random search. Compared with the traditional traversal method, which requires searching all possible parameter values ​​one by one and has higher complexity, the use of the cross-entropy iteration method to assist time-hopping code estimation and coherent merging can significantly reduce the number of searches and reduce the complexity of parameter estimation.

[0055] 2. The cross-entropy iteration-assisted time-hopping code estimation and coherent combining method and device disclosed in the present invention utilize cross-entropy iteration to accurately estimate the time-hopping code and the multi-hop carrier phase, and obtain a signal-to-noise ratio gain through multi-hop coherent combining. As the number of hops increases, the single-hop signal-to-noise ratio required to achieve the same demodulation bit error rate decreases, thereby reducing the requirement for the single-hop signal transmission power.

[0056] 3. In an open channel of satellite communication, there is a risk that wireless signals may be intercepted by non-cooperative parties. The present invention discloses a method and device for estimating and coherently combining time-hopping codes assisted by cross-entropy iteration. The communication signal transmission time is determined by a randomly changing time-hopping code, and a cross-entropy iteration method is used to obtain a global optimal vector group for time slot selection and carrier phase compensation. Time slot selection and carrier phase compensation are performed on the received signal based on the global optimal vector group obtained by random search, and the signal-to-noise ratio is improved by multi-hop coherent combining. By increasing the uncertainty of the communication signal in the time domain, the risk of satellite communication signals being intercepted by non-cooperative parties is reduced, and communication security is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] 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 prior art descriptions. Obviously, the drawings described below are some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0058] Figure 1 Flowchart of the joint estimation of time-hopping code and carrier phase assisted by cross-entropy iteration.

[0059] Figure 2 Block diagram of cross-entropy iteration-assisted time-hopping code estimation and multi-hop coherent combining.

[0060] Figure 3 This is a schematic diagram of time-hopping code.

[0061] Figure 4 Iteration curve for merging signal-to-noise ratio loss.

[0062] Figure 5 is the combined bit error rate assisted by cross entropy iteration. DETAILED DESCRIPTION

[0063] The present invention is further described and described in detail below with reference to the accompanying drawings and embodiments.

[0064] like Figure 1 As shown, the cross entropy iteration-assisted time hopping code estimation and multi-hop coherent combining method disclosed in this embodiment has the following specific implementation steps:

[0065] Step 1: The time slot structure of the time-hopping signal based on the time-hopping code is as follows: Figure 2 As shown, in this embodiment, N f =8,N h =4,N s =1000, generate BPSK modulated time-hopping signal as shown in formula (1), the 1000 BPSK modulation symbols to be sent are repeatedly transmitted in 8 time frames, each time frame is divided into 4 time slots, the time slot position of the signal sent in each time frame is determined by the time-hopping code, and the communication parties agree that the time-hopping code value range is c m ∈{0,1,2,3}, time-hopping code c m Add a time shift c to the signal of the mth time frame m T c .

[0066] Step 2: Send the BPSK modulated time-hopping signal obtained in step 1 into the AWGN channel, and receive the signal transmitted through the AWGN channel. The received signal after passing through the AWGN channel is shown in formula (2). The receiving end delay τ and frequency deviation f d Ideally synchronized.

[0067] Step 3: The initial phase search range of the carrier of each frame of the received signal is [0,2π). The two parties agree on c m The search range is {0, 1, 2, 3}. In this embodiment, D1=5, D2=2, N1=32, N2=4, and the initial phase of the carrier of the received signal of the mth frame and the time hopping code search parameters are respectively A mapping relationship is established between the search value and the binary code. Each carrier phase search value corresponds to a 5-bit binary number, and each time hopping code search value corresponds to a 2-bit binary number, thereby realizing parameter quantization of the time hopping code and the carrier phase of each hopping signal.

[0068] The initial phase estimate of the dth carrier of the mth frame is shown in formula (3). d-1 is represented as a 5-bit binary number. For example, d-1=10 is represented as the binary number 01010, thereby establishing φ m,d The mapping relationship between the u-th time hopping code estimation value of the m-th frame is shown in formula (4), where u-1 is represented as a 2-bit binary number, for example, u-1=2 is represented as the binary number 10, thereby establishing c m,u Mapping relationship with 2-bit binary numbers.

[0069] Step 4: Initialize the binary quantization bit generation probability as the input of the first cross entropy iteration. In this embodiment, the number of candidate groups N c =300, and 300 groups of binary codes are obtained according to the binary quantization bit generation probability, which are called candidate groups. The time hopping code estimation value and carrier phase estimation value are obtained by binary code mapping. The time slot where the signal is located is selected according to the time hopping code estimation value, and the signal carrier phase of the selected time slot is compensated according to the carrier phase estimation value, and the compensated multi-hop signals are coherently combined. The signal-to-noise ratio of the combined signal is estimated, and the difference between the estimated signal-to-noise ratio and the theoretical signal-to-noise ratio is calculated to obtain the combined signal-to-noise ratio loss, which is used as the objective function of the cross-entropy iteration.

[0070] In this embodiment, the binary quantization bits of the 8-frame time hopping code and the carrier phase estimation value total 56 bits. The probability of generating binary quantization bits in the i-th cross entropy iteration is in represents the probability that the jth quantization bit takes 1, given by The resulting binary quantization bits are represented as in represents the jth quantization bit, b i The mapped time hopping code and carrier phase estimation value are recorded as Initialize the binary quantization bit generation probability to Generate a binary code based on the probability to obtain the time hopping code and carrier phase estimation value. Select the time slot where the signal is located based on the time hopping code estimation value. Compensate the signal carrier phase of the selected time slot based on the carrier phase estimation value. Coherently combine the compensated multi-hop signals. According to formula (8), the theoretical signal-to-noise ratio of the combined signal is γ1+10log 10 8≈γ1+9, the combined signal-to-noise ratio loss is calculated according to formulas (9) and (10), and the estimated results of the combined signal-to-noise ratio loss of the 300 candidate groups are obtained.

[0071] Step 5: Use cross entropy to iteratively update the parameter estimation results, and sort the 300 combined signal-to-noise ratio losses obtained in step 4 from small to large to optimize the number of groups N. e =60 as an example, the time hopping codes and carrier phase quantization parameters corresponding to the first 60 groups with the smallest combined signal-to-noise ratio loss are selected as the preferred group, and the probability of each bit in the binary quantization bits of the preferred group taking 0 or 1 is calculated. According to the probability obtained by statistics of the preferred group, the binary code generation probability of the next cross entropy iteration is obtained.

[0072] Sort the 300 combined SNR loss estimation results from small to large, and record the combined SNR loss sorting result obtained by the i-th cross entropy iteration as The corresponding time hopping code and carrier phase binary quantization bits are recorded as l∈{1, 2, ..., N c}, select the first 60 groups of binary quantization bits with the smallest combined signal-to-noise ratio loss to form the preferred group The corresponding time hopping code and carrier phase estimation value are According to formula (11), the probability p of each quantization bit in the preferred group being 1 is calculated: i+1 , update the generation probability of the next iteration according to formula (12) In this embodiment, α=1, that is,

[0073] Step 6: By setting the global optimal vector group to avoid falling into the local optimal solution, the time hopping code and carrier phase estimation value with the smallest signal-to-noise ratio loss in the cross entropy iteration process are selected as the global optimal vector group. When each element in becomes 0 or 1, or the number of iterations reaches the set maximum number of iterations, the cross entropy iteration stops and the global optimal vector group is output. The received signal is time slot selected and carrier phase compensated according to the global optimal vector group obtained by random search, and the demodulation signal-to-noise ratio gain is obtained through multi-hop coherent combining.

[0074] set up Used to record the minimum combined signal-to-noise ratio loss from the 1st iteration to the i-th iteration, set As a record The corresponding time hopping code and carrier phase estimation value, when the N obtained in the i-th iteration in step 5 c The minimum value of the combined signal-to-noise ratio loss satisfies When Update the value to and Update the value to otherwise and No change. Calculation The number of elements in the number of 0 or 1 is M. When M < 56 and the current number of iterations is less than the set maximum number of iterations, As the input condition for the next cross entropy iteration, repeat steps 4 to 6. When M = 56 or the current number of iterations is equal to the set maximum number of iterations, the cross entropy iteration stops and the global optimal vector group is output.

[0075] like Figure 4 As shown, N c =300, change the ratio of the number of preferred groups to the number of candidate groups N e / N c , simulate the iterative convergence curve, and obtain the relationship between the average combined signal-to-noise ratio loss and the number of iterations. e / N c = 0.01, it can be converged after 5 iterations, and the combined signal-to-noise ratio loss is about 2.3dB. e / N c = 0.3, the combined signal-to-noise ratio loss is reduced to about 0.1 dB, and convergence is achieved after about 25 iterations. e / N c When N is smaller, the convergence speed is faster, but it is easy to converge to the local optimal solution. e / N c As increases, it is easy to obtain the global optimal solution, but the number of iterations increases and the complexity increases.

[0076] Figure 5 The cross-entropy iteration-assisted method compares the bit error rate with the ergodic method and the theoretical combination. The ergodic method performs a point-by-point search on the two-dimensional grid of the time-hopping code and the carrier phase. Ideally, this method can accurately estimate the discrete time-hopping code, and the performance loss comes from the grid search step of the carrier phase. The cross-entropy iteration-assisted method uses an adaptive key sampling strategy to randomly search on the two-dimensional grid of the time-hopping code and the carrier phase to reduce the number of grid searches. In this embodiment, the number of grids in the time-hopping code dimension of the ergodic method is 2 16 , the number of grids in the carrier phase dimension is 2 24 , then the traversal method searches for 2 16 ×2 24 =2 40 In the cross entropy iterative auxiliary method, set N c =300 and N e / N c = 0.2, converges after about 20 iterations, then the number of cross entropy iteration searches is about 300 × 20 = 6000, which is significantly reduced compared to the traversal method. Set the received signal carrier phase in the middle of the grid, and in the single-hop E b / N0 range is -6dB~1dB, under the condition of simulating demodulation bit error rate, such as Figure 5As shown in Figure 2, the demodulation performance of the cross entropy iteration-assisted method is improved by about 0.5 dB compared to the ergodic method (@BER = 1×10 -4 ), the performance loss compared to the theoretical combination is about 0.2dB (@BER=1×10 -4 ). Compared with the ergodic method, the cross entropy iteration-assisted method can improve the demodulation signal-to-noise ratio through multi-hop coherent combining with lower complexity, and has less loss than the theoretical combining, which effectively improves the reliability of time-hopping communication.

[0077] The specific description above further illustrates the purpose, technical solutions and beneficial effects of the invention in detail. It should be understood that the above is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for estimating time-hopping codes and combining multiple hops of coherent signals for satellite communications, characterized in that: The following steps are included: Step 1: Divide the communication time window into multiple time frames, each of which includes multiple time slots. After the information symbol to be sent is modulated by BPSK, it is repeatedly transmitted in the specified time slots of multiple time frames. The time slot position of the signal sent in each time frame is determined by the time hopping code corresponding to the frame. The communicating parties agree that the time hopping code changes randomly within a predetermined range, and generate a BPSK modulated time hopping signal with a random time hopping code. Step 2: Send the BPSK modulated time-hopping signal obtained in step 1 into the AWGN channel, and receive the signal transmitted through the AWGN channel; Step 3: The initial phase search range of the carrier of each frame of the received signal is [0,2π). The two parties agree on c m The search range is { 0 ,1,...,N h -1}, the initial phase of the carrier of the received signal of the mth frame and the time-hopping code search parameters are in A mapping relationship is established between the search value and the binary code. D1 and D2 are binary quantization bit numbers. Each carrier phase search value corresponds to a D1bit binary number, and each time hopping code search value corresponds to a D2bit binary number, that is, the parameter quantization of the time hopping code and the carrier phase of each hopping signal is realized; Step 4: Initialize the binary quantization bit generation probability as the input of the first cross entropy iteration, and obtain N according to the binary quantization bit generation probability c A group of binary codes is called a candidate group; a time hopping code estimation value and a carrier phase estimation value are obtained by mapping the binary code; a time slot where the signal is located is selected according to the time hopping code estimation value; the signal carrier phase of the selected time slot is compensated according to the carrier phase estimation value; and the compensated multi-hop signals are coherently combined; the signal-to-noise ratio of the combined signal is estimated, and the difference between the estimated signal-to-noise ratio and the theoretical signal-to-noise ratio is calculated to obtain the combined signal-to-noise ratio loss, and the combined signal-to-noise ratio loss is used as the objective function of the cross entropy iteration; Step 5: Use cross entropy to iteratively update the parameter estimation results and replace the N obtained in step 4 c Sort the combined signal-to-noise ratio losses from small to large, and select the top N with the smallest combined signal-to-noise ratio loss e The time hopping code and carrier phase quantization parameters corresponding to the group are taken as the preferred group, and the probability of each bit in the binary quantization bits of the preferred group taking 0 or 1 is calculated. According to the probability obtained by statistics of the preferred group, the probability of binary quantization bit generation in the next cross entropy iteration is obtained; Step 6: By setting the global optimal vector group to avoid falling into the local optimal solution, the time hopping code and carrier phase estimation value with the smallest signal-to-noise ratio loss in the cross entropy iteration process are selected as the global optimal vector group. When each element in becomes 0 or 1, or the number of iterations reaches the set maximum number of iterations, the cross entropy iteration stops and the global optimal vector group is output; the time slot selection and carrier phase compensation of the received signal are performed according to the global optimal vector group obtained by random search, and the demodulation signal-to-noise ratio is improved through multi-hop coherent combining, so as to effectively improve the reliability of time-hopping communication with low complexity.

2. The method for satellite communication-oriented time hopping code estimation and multi-hop coherent combining as claimed in claim 1, characterized in that: In step one, The BPSK modulated time-hopping signal with random time-hopping code is generated as shown below: N to be sent s Symbols in N f The transmission is repeated in time frames, and the duration of a single time frame is T f , b k represents the kth BPSK modulation symbol, b k ∈{-1,+1}, w(t) represents a single pulse waveform, c m Indicates the time-hopping code of the mth time frame, c m ∈{0,1,...,N h -1}, time-hopping code c m Add a time shift c to the signal of the mth time frame m T c , N h T c =T f , T s is the duration of a single symbol, T c =N s T s , f0 is the carrier frequency of the transmitted signal, φ 0,m It is the initial phase of the transmitted signal carrier in the mth time frame.

3. The method for satellite communication-oriented time hopping code estimation and multi-hop coherent combining as claimed in claim 2, characterized in that: In step 2, The received signal after passing through the AWGN channel is expressed as Where A is the amplitude of the transmitted signal when it reaches the receiver, τ is the delay of the receiving end relative to the transmitting end, and f d is the frequency deviation of the received signal relative to the transmitted signal, φ m is the initial phase of the carrier of the received signal in the mth time frame, n(t) represents additive complex Gaussian white noise, with a mean of 0 and a variance of Receiver delay τ and frequency offset f d Ideally synchronized.

4. The method for satellite communication-oriented time hopping code estimation and multi-hop coherent combining as claimed in claim 3, characterized in that: In step three, φ m,d represents the initial phase estimate of the d-th carrier of the m-th frame, d∈{1,2,...,N1}, and Represent d-1 as a binary number of D1 bits, and then establish φ from the above formula m,d The mapping relationship with the D1bit binary number; c m,u represents the u-th time hopping code estimate of the m-th frame, u∈{1, 2, ..., N2}, and N2=N h ,have c m,u =u-1 (4) Represent u-1 as a D2-bit binary number, and then establish c from the above formula m,u The mapping relationship with D2bit binary number.

5. The method for satellite communication-oriented time hopping code estimation and multi-hop coherent combining as claimed in claim 4, characterized in that: In step four, N f The total number of binary quantization bits of the frame hopping code and the carrier phase estimation value is N f (D1+D2) bits, the probability of generating binary quantization bits for the i-th cross entropy iteration is in represents the probability that the jth quantization bit takes 1, given by The resulting binary quantized bits are represented as in represents the jth quantization bit, b i The mapped time hopping code and carrier phase estimation value are recorded as Initialize the binary quantization bit generation probability to in Indicates size is 1×N f (D1+D2), a vector with all elements being 1, generating a binary code according to the probability, obtaining a time hopping code and a carrier phase estimation value, selecting a time slot where the signal is located according to the time hopping code estimation value, compensating the signal carrier phase of the selected time slot according to the carrier phase estimation value, and coherently combining the compensated multi-hop signals; The time shift in the mth frame is v m T c The kth data in a time slot is expressed as Among them C m (v m ) is the time-hopping code indicator function Estimated value based on time-hopping code Select the time slot position where the mth frame signal is located, and calculate the carrier phase estimate value Compensate the carrier phase of the selected time slot in the mth frame, N f The signal after the kth data of the selected time slot of the time frame is combined is expressed as Let γ1 represent the single-hop signal-to-noise ratio, then the theoretical signal-to-noise ratio after merging is c comb =γ1+10log 10 (N f ) (8) The difference between the estimated signal-to-noise ratio and the theoretical signal-to-noise ratio is calculated according to the following formula, and the combined signal-to-noise ratio loss is obtained as follows: in, In order to actually combine the estimated results of the signal-to-noise ratio, the signal-to-noise ratio estimation method used is: Among them, mean() means taking the mean, and var() means taking the variance; The estimated results of the combined theoretical signal-to-noise ratio and the actual combined signal-to-noise ratio are substituted into the combined signal-to-noise ratio loss formula to calculate the combined signal-to-noise ratio loss. The calculated combined signal-to-noise ratio loss is used as the objective function of the cross entropy iteration. c Group parameters to get N c The combined signal-to-noise ratio loss estimation results.

6. The method for satellite communication-oriented time hopping code estimation and multi-hop coherent combining as claimed in claim 5, characterized in that: In step five, N c The combined signal-to-noise ratio loss estimation results are sorted from small to large, and the combined signal-to-noise ratio loss sorting result obtained by the i-th cross entropy iteration is recorded as The corresponding time hopping code and carrier phase binary quantization bits are recorded as Depend on The estimated value obtained by mapping is recorded as Take the top N with the smallest combined signal-to-noise ratio loss e Group binary quantization bits into preferred groups The corresponding time hopping code and carrier phase estimation value are Calculate the probability p of each quantized bit in the preferred group being 1 i+1 P i+1 Perform smoothing and update the generation probability of the next iteration Among them, α is the smoothing coefficient, α∈(0,1], the larger the α, the faster the convergence speed.

7. The method for satellite communication-oriented time hopping code estimation and multi-hop coherent combining as claimed in claim 6, characterized in that: The implementation method of step six is: set up Used to record the minimum combined signal-to-noise ratio loss from the 1st iteration to the i-th iteration, set As a record The corresponding time hopping code and carrier phase estimation value, when the N obtained in the i-th iteration in step 5 c The minimum value of the combined signal-to-noise ratio loss satisfies When Update the value to and Update the value to otherwise and unchanged; calculated The number of elements in is 0 or 1, when M<N f (D1+D2) and the current number of iterations is less than the set maximum number of iterations, As the input condition for the next cross entropy iteration, repeat steps 4 to 6; when M = N f (D1+D2) or when the current number of iterations is equal to the set maximum number of iterations, the cross entropy iteration stops and the global optimal vector group is output. According to the time-hopping code and carrier phase estimation values ​​in the global optimal vector group obtained by the above random search process, time slot selection and carrier phase compensation are performed on the received signal, and the compensated multi-hop signals are coherently combined to improve the demodulation signal-to-noise ratio, thereby effectively improving communication reliability with low complexity.

8. A time hopping code estimation and multi-hop coherent combining device for satellite communication, used to implement the time hopping code estimation and multi-hop coherent combining method for satellite communication as claimed in claim 1, 2, 3, 4, 5, 6 or 7, characterized in that: It includes parameter quantization unit, parameter compensation and multi-hop merging unit, signal-to-noise ratio estimation unit, and cross entropy iteration unit; The parameter quantization unit is used to establish a mapping relationship between the time hopping code and the carrier phase search value and the binary quantization bit; The parameter compensation and multi-hop merging unit performs parameter compensation and multi-hop merging based on the estimation result obtained by the cross entropy iteration unit, selects the time slot where the signal is located according to the time hopping code estimation value, compensates the carrier phase of the selected time slot signal according to the carrier phase estimation value, and coherently combines the compensated multi-hop signals; The signal-to-noise ratio estimation unit estimates the signal-to-noise ratio of the combined signal obtained by the parameter compensation and combining unit, calculates the difference between the estimated signal-to-noise ratio and the theoretical signal-to-noise ratio, and obtains the combined signal-to-noise ratio loss; The cross entropy iteration unit generates a binary code from a binary quantization bit generation probability, generates a time hopping code and a carrier phase estimation value according to the binary code and a mapping relationship obtained by the parameter quantization unit, outputs the estimation value to the parameter compensation and multi-hop merging unit, takes the combined signal-to-noise ratio loss calculated by the signal-to-noise ratio estimation unit as an objective function, selects samples with a smaller combined signal-to-noise ratio loss as a preferred group, regenerates the binary quantization bit generation probability for the next iteration according to the preferred group, records the time hopping code and the carrier phase estimation value corresponding to the minimum combined signal-to-noise ratio loss as a global optimal vector group during the iteration process, and outputs the global optimal vector group after the iteration stops.

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