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implementation of the ray backpropagation method  (MathWorks Inc)


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    Structured Review

    MathWorks Inc implementation of the ray backpropagation method
    Estimates of range and depth of a simulated source at 10 m depth, between a 100 and 900 m range from the receiver. The <t> backpropagation </t> method was applied to the four echoes, the earlier two echoes (1& 2) and the last two echoes (1& 2). The source image method was applied to the earlier two echoes. The range and depth estimates were obtained using estimates of the elevation angles from simulated data with 5 dB SNR.
    Implementation Of The Ray Backpropagation Method, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/implementation of the ray backpropagation method/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    implementation of the ray backpropagation method - by Bioz Stars, 2026-03
    90/100 stars

    Images

    1) Product Images from "Experimental Results of Underwater Cooperative Source Localization Using a Single Acoustic Vector Sensor"

    Article Title: Experimental Results of Underwater Cooperative Source Localization Using a Single Acoustic Vector Sensor

    Journal: Sensors (Basel, Switzerland)

    doi: 10.3390/s130708856

    Estimates of range and depth of a simulated source at 10 m depth, between a 100 and 900 m range from the receiver. The backpropagation method was applied to the four echoes, the earlier two echoes (1& 2) and the last two echoes (1& 2). The source image method was applied to the earlier two echoes. The range and depth estimates were obtained using estimates of the elevation angles from simulated data with 5 dB SNR.
    Figure Legend Snippet: Estimates of range and depth of a simulated source at 10 m depth, between a 100 and 900 m range from the receiver. The backpropagation method was applied to the four echoes, the earlier two echoes (1& 2) and the last two echoes (1& 2). The source image method was applied to the earlier two echoes. The range and depth estimates were obtained using estimates of the elevation angles from simulated data with 5 dB SNR.

    Techniques Used:

    Source localization results for the scenario of using the backpropagation method for source range and depth, 900m and 10 m, respectively and SNR = 5 dB: true source and receiver position (represented by the star) and backpropagated rays ( a ), ambiguity curves ( σ ) and source-localization plot considering four rays ( b ) and two rays ( c ). The arrows in plots ( b ) and ( c ) indicate the estimated source position (upper plots) and the corresponding minimum of the ambiguity curve (lower plots).
    Figure Legend Snippet: Source localization results for the scenario of using the backpropagation method for source range and depth, 900m and 10 m, respectively and SNR = 5 dB: true source and receiver position (represented by the star) and backpropagated rays ( a ), ambiguity curves ( σ ) and source-localization plot considering four rays ( b ) and two rays ( c ). The arrows in plots ( b ) and ( c ) indicate the estimated source position (upper plots) and the corresponding minimum of the ambiguity curve (lower plots).

    Techniques Used:

    Source range and depth estimates at various instants of the Makai'05 field calibration event using the ray backpropagation method and the image method. The column marked, σ , represents the minimum of the square root value of the objective function used with the backpropagation method. The true source depth is 10 m. The estimated range values compare with the GPS fixes in <xref ref-type= Figure 10 ." title="... of the Makai'05 field calibration event using the ray backpropagation method and the image method. ..." property="contentUrl" width="100%" height="100%"/>
    Figure Legend Snippet: Source range and depth estimates at various instants of the Makai'05 field calibration event using the ray backpropagation method and the image method. The column marked, σ , represents the minimum of the square root value of the objective function used with the backpropagation method. The true source depth is 10 m. The estimated range values compare with the GPS fixes in Figure 10 .

    Techniques Used:



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    implementation of the ray backpropagation method  (MathWorks Inc)
    90
    MathWorks Inc implementation of the ray backpropagation method
    Estimates of range and depth of a simulated source at 10 m depth, between a 100 and 900 m range from the receiver. The <t> backpropagation </t> method was applied to the four echoes, the earlier two echoes (1& 2) and the last two echoes (1& 2). The source image method was applied to the earlier two echoes. The range and depth estimates were obtained using estimates of the elevation angles from simulated data with 5 dB SNR.
    Implementation Of The Ray Backpropagation Method, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/implementation of the ray backpropagation method/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    implementation of the ray backpropagation method - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    Estimates of range and depth of a simulated source at 10 m depth, between a 100 and 900 m range from the receiver. The backpropagation method was applied to the four echoes, the earlier two echoes (1& 2) and the last two echoes (1& 2). The source image method was applied to the earlier two echoes. The range and depth estimates were obtained using estimates of the elevation angles from simulated data with 5 dB SNR.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Experimental Results of Underwater Cooperative Source Localization Using a Single Acoustic Vector Sensor

    doi: 10.3390/s130708856

    Figure Lengend Snippet: Estimates of range and depth of a simulated source at 10 m depth, between a 100 and 900 m range from the receiver. The backpropagation method was applied to the four echoes, the earlier two echoes (1& 2) and the last two echoes (1& 2). The source image method was applied to the earlier two echoes. The range and depth estimates were obtained using estimates of the elevation angles from simulated data with 5 dB SNR.

    Article Snippet: Model-based source localization methods are, in general, not considered for real-time implementations, because of the time needed to compute the optimization procedure, which requires a large number of forward model runs, but a non-optimized Matlab implementation of the ray backpropagation method took less than 4 s in a current laptop.

    Techniques:

    Source localization results for the scenario of using the backpropagation method for source range and depth, 900m and 10 m, respectively and SNR = 5 dB: true source and receiver position (represented by the star) and backpropagated rays ( a ), ambiguity curves ( σ ) and source-localization plot considering four rays ( b ) and two rays ( c ). The arrows in plots ( b ) and ( c ) indicate the estimated source position (upper plots) and the corresponding minimum of the ambiguity curve (lower plots).

    Journal: Sensors (Basel, Switzerland)

    Article Title: Experimental Results of Underwater Cooperative Source Localization Using a Single Acoustic Vector Sensor

    doi: 10.3390/s130708856

    Figure Lengend Snippet: Source localization results for the scenario of using the backpropagation method for source range and depth, 900m and 10 m, respectively and SNR = 5 dB: true source and receiver position (represented by the star) and backpropagated rays ( a ), ambiguity curves ( σ ) and source-localization plot considering four rays ( b ) and two rays ( c ). The arrows in plots ( b ) and ( c ) indicate the estimated source position (upper plots) and the corresponding minimum of the ambiguity curve (lower plots).

    Article Snippet: Model-based source localization methods are, in general, not considered for real-time implementations, because of the time needed to compute the optimization procedure, which requires a large number of forward model runs, but a non-optimized Matlab implementation of the ray backpropagation method took less than 4 s in a current laptop.

    Techniques:

    Source range and depth estimates at various instants of the Makai'05 field calibration event using the ray backpropagation method and the image method. The column marked, σ , represents the minimum of the square root value of the objective function used with the backpropagation method. The true source depth is 10 m. The estimated range values compare with the GPS fixes in <xref ref-type= Figure 10 ." width="100%" height="100%">

    Journal: Sensors (Basel, Switzerland)

    Article Title: Experimental Results of Underwater Cooperative Source Localization Using a Single Acoustic Vector Sensor

    doi: 10.3390/s130708856

    Figure Lengend Snippet: Source range and depth estimates at various instants of the Makai'05 field calibration event using the ray backpropagation method and the image method. The column marked, σ , represents the minimum of the square root value of the objective function used with the backpropagation method. The true source depth is 10 m. The estimated range values compare with the GPS fixes in Figure 10 .

    Article Snippet: Model-based source localization methods are, in general, not considered for real-time implementations, because of the time needed to compute the optimization procedure, which requires a large number of forward model runs, but a non-optimized Matlab implementation of the ray backpropagation method took less than 4 s in a current laptop.

    Techniques: