Abstract: The present invention discloses is a multi-band hyperbolic frequency modulation spread spectrum communication method based on cross sub-band division. In the present solution, multi-band division of different sub-band quantities is performed on an available bandwidth of an underwater acoustic system according to the parity of the serial number of the current spread spectrum period to achieve the aim of cross sub-band division. On this basis, a plurality of divided sub-bands are grouped in pairs; for each group, sub-band selection is performed according to different transmitted data by using a sub-band selection and activation method to realize multi-band parallel transmission. Meanwhile, in each spread spectrum period, an activated sub-band performs frequency modulation on a modulated signal by using rising and falling hyperbolic frequency modulation signals respectively.

Abstract: Disclosed by the present invention is a sub-band selection activation-based multi-band hyperbolic frequency modulation spread spectrum underwater acoustic communication method. The present invention discloses: dividing the available bandwidth of an underwater acoustic system into a plurality of sub-bands, performing hyperbolic frequency modulation on each of the sub-bands respectively, and performing spread spectrum modulation on the plurality of sub-bands within the same frequency modulation period, thus implementing multi-band parallel transmission. Hence, within each frequency modulation period, the divided plurality of sub-bands is grouped, and each sub-band group activates different sub-bands for transmission according to different options for transmitting data. Compared to other underwater acoustic hyperbolic frequency modulation communication solutions, the present invention further improves the frequency band utilization of the system, and the energy efficiency is also improved.

Abstract: The invention provides a frequency offset estimation method for an OFDM-IM system. The method includes: S1. performing preliminary frequency offset compensation on a received signal subjected to non-uniform frequency offset by using a two-step method of: (1) resampling and down conversion; and (2) unified compensation for residual frequency offset ?, wherein in the step (2), a sum of energy of null sub-carriers is used as a cost function, an initial estimation value of ? is obtained by one-dimensional search, and the preliminary compensation is performed; S2. estimating positions of non-activated sub-carriers in the OFDM-IM system by using the signal subjected to the preliminary compensation; and S3. assigning certain weights to the estimated sub-carriers, adding energy of the estimated sub-carriers into the cost function according to different weights, obtaining a final estimation value of ? by the one-dimensional search performed on ?, and performing secondary compensation.

Abstract: The invention provides a method for automatically identifying a modulation mode for a digital communication signal. The method comprises the following steps of: S1: preprocessing a training digital modulation signal; S2: extracting a characteristic value of the training digital modulation signal; S3: constructing a strong classifier by Bagging learning; and S4: preprocessing a modulation signal to be tested and extracting a corresponding characteristic parameter, and then inputting the characteristic parameter into the strong classifier in the S3 to classify and identify the modulation signal. According to the method, by processing all characteristic values in parallel, a success rate of identification has little to do with an identification performance of a single characteristic parameter and is mainly related to an overall performance, so that the identification to the modulation mode has the advantages of fast identification speed and high success rate of identification.

Abstract: The invention provides a frequency offset estimation method for an OFDM-IM system. The method includes: S1. performing preliminary frequency offset compensation on a received signal subjected to non-uniform frequency offset by using a two-step method of: (1) resampling and down conversion; and (2) unified compensation for residual frequency offset ?, wherein in the step (2), a sum of energy of null sub-carriers is used as a cost function, an initial estimation value of ? is obtained by one-dimensional search, and the preliminary compensation is performed; S2. estimating positions of non-activated sub-carriers in the OFDM-IM system by using the signal subjected to the preliminary compensation; and S3. assigning certain weights to the estimated sub-carriers, adding energy of the estimated sub-carriers into the cost function according to different weights, obtaining a final estimation value of ? by the one-dimensional search performed on ?, and performing secondary compensation.

Abstract: Disclosed by the present invention is a sub-band selection activation-based multi-band hyperbolic frequency modulation spread spectrum underwater acoustic communication method. The present invention discloses: dividing the available bandwidth of an underwater acoustic system into a plurality of sub-bands, performing hyperbolic frequency modulation on each of the sub-bands respectively, and performing spread spectrum modulation on the plurality of sub-bands within the same frequency modulation period, thus implementing multi-band parallel transmission. Hence, within each frequency modulation period, the divided plurality of sub-bands is grouped, and each sub-band group activates different sub-bands for transmission according to different options for transmitting data. Compared to other underwater acoustic hyperbolic frequency modulation communication solutions, the present invention further improves the frequency band utilization of the system, and the energy efficiency is also improved.

Abstract: The invention provides a method for automatically identifying a modulation mode for a digital communication signal. The method comprises the following steps of: S1: preprocessing a training digital modulation signal; S2: extracting a characteristic value of the training digital modulation signal; S3: constructing a strong classifier by Bagging learning; and S4: preprocessing a modulation signal to be tested and extracting a corresponding characteristic parameter, and then inputting the characteristic parameter into the strong classifier in the S3 to classify and identify the modulation signal. According to the method, by processing all characteristic values in parallel, a success rate of identification has little to do with an identification performance of a single characteristic parameter and is mainly related to an overall performance, so that the identification to the modulation mode has the advantages of fast identification speed and high success rate of identification.

Abstract: Disclosed are an adaptive RLS decision feedback equalizing system, characterized by comprising: an error code cross-correlation module, an equalization module, a decision feedback unit, a coefficient updating unit and an autocorrelation estimation module. Also disclosed are an implementation method of the adaptive RLS decision feedback equalizing system, comprising the following steps: 1) setting an initial value of c0 for a filtering coefficient; 2) generating a filtering output signal yk; 3) computing an error code cross-correlation result Ik; 4) updating the filtering coefficient ck?1 to ck; 5) updating an autocorrelation inverse matrix estimation result Pk?1 to Pk according to a forget constant factor w and an equalizer input signal sequence rk; 6) repeating step 2) to step 5), until the equalizer coefficient converges.

Abstract: Disclosed is an underwater source node positioning method, which includes the specific steps: (1) placing distributed underwater receiving nodes, the source node transmitting a pulse signal, and the receiving nodes receiving the pulse signal sent by the source node; (2) processing the signal of each receiving node; (3) according to a multipath signal received by each receiving node, performing parameter estimation of the position of the source node, specifically: (3-1) calculating a path length of each path; (3-2) calculating a delay difference between each path and a direct path; (3-3) calculating the signal received by each receiving node; (3-4) performing mesh search matching to obtain the position of the source node. Compared with the conventional method, the present invention requires fewer receiving nodes and does not require accurate clock synchronization of signals. The present invention utilizes multipath signals propagated by signals to enable more accurate positioning of the source nodes.

Abstract: Disclosed are an adaptive RLS decision feedback equalizing system, characterized by comprising: an error code cross-correlation module, an equalization module, a decision feedback unit, a coefficient updating unit and an autocorrelation estimation module. Also disclosed are an implementation method of the adaptive RLS decision feedback equalizing system, comprising the following steps: 1) setting an initial value of c0 for a filtering coefficient; 2) generating a filtering output signal yk; 3) computing an error code cross-correlation result Ik; 4) updating the filtering coefficient ck?1 to ck; 5) updating an autocorrelation inverse matrix estimation result Pk?1 to Pk according to a forget constant factor w and an equalizer input signal sequence rk; 6) repeating step 2) to step 5), until the equalizer coefficient converges.