KR20170082080A - Method and Apparatus for applying variable data map and variable statistic characteristics information for identifying underwater fixed target and clutter - Google Patents

Method and Apparatus for applying variable data map and variable statistic characteristics information for identifying underwater fixed target and clutter Download PDF

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KR20170082080A
KR20170082080A KR1020160001252A KR20160001252A KR20170082080A KR 20170082080 A KR20170082080 A KR 20170082080A KR 1020160001252 A KR1020160001252 A KR 1020160001252A KR 20160001252 A KR20160001252 A KR 20160001252A KR 20170082080 A KR20170082080 A KR 20170082080A
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signal
variable
data
data map
target
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KR101813357B1 (en
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서익수
김성원
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국방과학연구소
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/88—Sonar systems specially adapted for specific applications
    • G01S15/89—Sonar systems specially adapted for specific applications for mapping or imaging
    • G01S15/8906—Short-range imaging systems; Acoustic microscope systems using pulse-echo techniques
    • G01S15/8979—Combined Doppler and pulse-echo imaging systems
    • G01S15/8981—Discriminating between fixed and moving objects or between objects moving at different speeds, e.g. wall clutter filter
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
    • G01S7/52004—Means for monitoring or calibrating
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
    • G01S7/52017—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00 particularly adapted to short-range imaging
    • G01S7/52046—Techniques for image enhancement involving transmitter or receiver
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
    • G01S7/52017—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00 particularly adapted to short-range imaging
    • G01S7/52077—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00 particularly adapted to short-range imaging with means for elimination of unwanted signals, e.g. noise or interference

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • General Physics & Mathematics (AREA)
  • Acoustics & Sound (AREA)
  • Measurement Of Velocity Or Position Using Acoustic Or Ultrasonic Waves (AREA)

Abstract

According to an embodiment of the present invention, there is provided an image processing apparatus including: a receiving unit for receiving a data signal generated from a sonar; A signal processor for detecting a target by pre-processing a received data signal and determining a variable data map and variable statistical feature information according to a detection distance and a signal size of the detected data to remove clutter; A fixed target tracking unit for tracking and tracking the fixed target using clutter-free detection data; And a screen processing unit for displaying the tracking result and the detection result. The apparatus for applying the variable data map and the variable statistical feature information may further comprise:

Description

FIELD OF THE INVENTION [0001] The present invention relates to a method and apparatus for applying variable data maps and variable statistical feature information for underwater fixed targets and clutter identification,

The present invention relates to underwater fixed target detection techniques, and more particularly, to a method and apparatus for removing clutters for improved fixed target detection in an active sonar system.

As the submergence of target underwater develops, it is a tendency to transmit the sound wave using active sonar rather than the target detection using the conventional passive sonar, and to detect the target with the reflected signal therefrom.

However, since the target is detected by the reflection signal of the sound wave, in addition to the target signal, non-target signals reflected on sea level, seafloor, aquatic life group also exist.

Generally, these non-target signals are referred to as clutter, which degrades the detection and tracking performance of the active sonar system and presents many difficulties for the operator to distinguish the target from the clutter on the display screen.

In order to solve this problem, many studies have been conducted to remove the clutter and keep the target signal intact. In this study, we propose a method to distinguish the target from the clutter by observing the continuity of the signal in the physical moveable space of the target, cumulatively processing the signal according to the detection cycle (Geometric Processing, etc.).

Recently, a method of distinguishing a target from a clutter using a statistical characteristic of a three-dimensional shape of a signal reflected in a single ping has been proposed.

However, these measures are very specific to maneuvering underwater vehicles and, in the case of underwater fixed targets, the ability to distinguish between targets and clutters is greatly reduced. In particular, if the target is cluttered and the received signal is accumulated according to the detection cycle and the continuity is observed, the distinction between the underwater fixed target and the clutter becomes more difficult.

In addition, it is not easy to distinguish the statistical characteristics of underwater fixed target and clutter, unlike the underwater maneuvering target, even if statistical features possessing the three-dimensional shape of the signal are extracted.

1. Korean Patent Publication No. 10-2014-0040422 2. Korean Patent Publication No. 10-2007-0016392

1. Yang Jin-mo et al., "Analysis of Detection Performance of Radar Signal Processor by Target Doppler Velocity and Clutter Spectrum Characteristics", Journal of Korea Electromagnetic Engineering Society, Vol. 22, No. 1 (January 2011) pp.47-58. 2. Kim, Yong, "A Study on Target Detection and Tracking Performance Improvement Using Target Identification Technique in Clutter Environment", Hanyang University, 2009

It is an object of the present invention to provide a method and an apparatus for removing a clutter for improving fixed target detection in an active sonar system.

SUMMARY OF THE INVENTION The present invention provides a method for removing clutters for improved underwater fixed target detection in an active sonar system in order to accomplish the above problems.

The method of removing the clutter includes:

A receiver for receiving a data signal generated from the sonar;

A signal processor for detecting a target by pre-processing the received data signal, determining a variable data map and variable statistical characteristic information according to a detection result, and post-processing the processed data signal;

A fixed target tracking unit for tracking the fixed target by applying the determined variable data map and the variable statistical characteristic information to generate a tracking result; And

And a screen processing unit for displaying the tracking result and the detection result.

The signal processor may include a preprocessor for generating preprocessed signal processing data by limiting a received data signal to a specific range using a preprocessing filter; A target detection unit for detecting a target from the signal processing data to generate detection data; A data map determining unit for determining a data map size by extracting a distance and a signal size from the detected data and setting a variable data map; And a fixed target post-processing unit for extracting the variable statistical feature information based on the set variable data map and removing the clit signal using the variable statistical feature information.

The data map discriminator may further include a peak signal search unit for extracting a distance and a signal size of the echo signal by scanning a peak having a center value larger than a peripheral value in a specific area from the detected data; A distance determination unit for determining a distance of the extracted echo signal; A signal size discrimination unit for discriminating the extracted signal size; And a data map determining unit configured to set a data map according to the distance of the discriminated echo signal and the determined signal magnitude.

In addition, the variable statistical feature information may include a distance of the fixed target in the water and a reflection signal characteristic according to a change in the marine environment.

In this case, the fixed target post-processing unit may include: a fixed target feature information extracting unit for extracting a median value and a variance value based on the data map; A fixed target shape estimator for generating a shape estimation result by estimating a shape of a signal by combining the median value and the variance value according to the distance and the signal size of the extracted echo signal; And a fixed target clutter determiner for classifying the shape estimation result into a target signal and a clutter signal using a linear classifier, and removing the clutter signal.

Also, the shape estimation result may be calculated by calculating a variance value for each region in the variable data map when the distance of the echo signal is close to and the magnitude is large.

Alternatively, when the distance of the echo signal is long and the size of the echo signal is small, the shape estimation result may be calculated by calculating the median slope and the dispersion value slope between adjacent regions in the variable data map.

Also, the classification of the clutter signal and the target signal may be classified into a clutter signal if the threshold value is greater than or equal to the threshold value and a clutter signal if the threshold value is less than the threshold value, And may be differently applied depending on the type of sound waves.

On the other hand, another embodiment of the present invention is a method for controlling a receiver, comprising: receiving a data signal generated by a receiver from a sonar; The signal processing unit preprocessing the received data signal to generate a result of detecting the target; A post-processing step of the signal processing unit determining the variable data map and the variable statistical feature information according to the detection distance and the signal amplitude of the peak signal based on the detection result and removing the clutter; Tracking the fixed target using the detection data of the fixed target tracking unit clutter removed and generating the tracking result; And displaying the detection result and the tracking result by the screen processing unit. The method may further include applying the variable data map and the variable statistical feature information.

According to the present invention, by applying variable data map and variable statistical feature information for underwater fixed target and clutter identification, the performance of distinguishing between target and clutter in the case of underwater fixed target is improved compared with the existing technique.

Another effect of the present invention is that it is particularly advantageous to distinguish between target and clutter when applied together with the case where the received signal is accumulated and the continuity is observed to distinguish the target from the clutter according to the detection cycle .

Another advantage of the present invention is that it is easy to classify the target and clutter statistical features in a manner similar to the conventional technique for the underwater maneuvering target using the statistical characteristics of the three-dimensional shape of the signal .

FIG. 1 is a block diagram of an apparatus for applying a variable data map and variable statistical feature information for an underwater fixed target and clutter identification according to an exemplary embodiment of the present invention. Referring to FIG.
2 is a detailed block diagram of the signal processing unit 200 shown in FIG.
FIG. 3 is a detailed block diagram of the data map determining unit 230 shown in FIG. 2, and is a block diagram for applying a data map variably to identify an underwater fixed target from a clutter in an active sonar.
FIG. 4 is a detailed block diagram of the fixed target post-processing unit 240 shown in FIG. 2. In the active sonar, statistical feature information is variably applied to distinguish clutter from fixed target and clutter, Fig.
5 is a flowchart illustrating a process of applying a variable data map and variable statistical feature information for underwater fixed target and clutter identification according to an embodiment of the present invention.

While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail. It is to be understood, however, that the invention is not to be limited to the specific embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

Like reference numerals are used for similar elements in describing each drawing.

The terms first, second, etc. may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another.

For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component. The term "and / or" includes any combination of a plurality of related listed items or any of a plurality of related listed items.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted as either ideal or overly formal in the sense of the present application Should not.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Reference will now be made in detail to the preferred embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the like elements throughout.

Prior to this, the data map is defined as follows.

A data map is a two-dimensional map in which an X-axis and a Y-axis are constituted by a distance bin and an azimuth beam around a peak of an echo signal in an active sonar, and each cell in the two-dimensional map has a size of an acoustic signal.

One embodiment of the present invention provides a method and apparatus for distinguishing an underwater fixed target from a clutter in an active sonar system. In particular, we distinguish the target and clutter based on the statistical characteristics of the signal shape reflected in the existing single ping. However, we provide a method to variably apply the data map size and variably apply the statistical features .

In an embodiment of the present invention, the data map size and statistical characteristic information are applied differently according to the distance and the signal size of the echo signal with respect to the active signal to distinguish the target of interest from the clutter of interest. A method and apparatus are provided for identifying and removing clutters and then tracking them to separate underwater fixed targets and clutters from active sonar systems.

FIG. 1 is a block diagram of an apparatus for applying a variable data map and variable statistical feature information for an underwater fixed target and clutter identification according to an exemplary embodiment of the present invention. Referring to FIG. Referring to FIG. 1, an apparatus for distinguishing between an underwater fixed target and a clutter includes a receiver 100 for receiving a data signal generated from a sonar (not shown), a processor for detecting a target by pre-processing the received data signal, A signal processing unit 200 for determining and post-processing a variable data map and variable statistical feature information according to the detection distance and signal size, a fixed target tracking unit 300 for tracking fixed targets using the clutter- A screen processing unit 400 for displaying detected data of the signal processing unit 200 and tracking data of the fixed target tracking unit 300, and the like.

2 is a detailed block diagram of the signal processing unit 200 shown in FIG. 2, the signal processing unit 200 includes a preprocessing unit 210 for generating signal processing data for limiting a received data signal to a specific range using a preprocessing filter and preventing a phenomenon such as superimposition, A data map determining unit 230 for determining a data map size by extracting a distance and a signal size from the detected data to set a data map, And a fixed target post-processing unit 240 for classifying the target signal and the clutter signal and removing the clutter signal.

FIG. 3 is a detailed block diagram of the data map determining unit 230 shown in FIG. 2, and is a configuration block diagram for applying a data map variably to identify an underwater fixed target from a clutter in an active sonar. 3, the data map determining unit 230 for applying the variable data map includes a peak signal searching unit 231, a distance determining unit 232, a signal size determining unit 233, and a data map determining unit 234, . The detailed operation of these will be described as follows.

The peak signal search unit 231 scans a position (i.e., a peak) where the center value is larger than the periphery in the 3x3 region.

Figure pat00001

The distance determining unit 232 and the signal size determining unit 233 determine the distance and the signal size of the echo signal with respect to the peak extracted by the peak signal searching unit 231. Distance

Figure pat00002
And the signal size is determined from a signal-to-noise ratio (SNR) dB value that is greater than zero.

The determined distance and signal size are used for data map size determination in the data map determination unit 234 in association with the corresponding peak. The setting of the data map is different according to the distance of the echo signal and the signal size.

Figure pat00003

Here, r denotes a distance, and b denotes an azimuth (beam), which means the x-axis and the y-axis of the data map, respectively. l n = 2 < n + 1 >

Figure pat00004
For example, l 1 means a 3 x 3 region, and l 2 means a 5 x 5 region.

For example, if the distance of the echo signal is short and the signal size is large, 3x3 (

Figure pat00005
) A set of region data
Figure pat00006
, 5x5 (
Figure pat00007
) A set of region data
Figure pat00008
And the feature information extracting unit 241
Figure pat00009
and
Figure pat00010
It is possible to extract the feature information from the feature information.

When the distance of the echo signal is long and the size of the signal is small, the fixed target post-processing unit 240

Figure pat00011
and
Figure pat00012
Except for that,
Figure pat00013
Wow
Figure pat00014
or
Figure pat00015
Wow
Figure pat00016
The feature information can be extracted from the data map. This is due to the distance of the fixed target in the water and the reflection signal characteristics due to various marine environment changes.

FIG. 4 is a detailed block diagram of the fixed target post-processing unit 240 shown in FIG. 2. In the active sonar, a configuration block for identifying clutters by applying statistical characteristic information variably to distinguish the fixed target from the clutter in the active sonar . Referring to FIG. 4, the detailed operation of the fixed target post-processing unit 240 is as follows.

The fixed target feature information extracting unit 241 extracts the median value and the variance value based on the respective data map settings reflecting the distance and signal size of the echo signal. The shape of the signal is estimated by combining the median value and the variance value according to the detection distance and the signal magnitude of the echo signal in the fixed target type up-converting unit 242. For example, when the distance of the echo signal is short and the signal size is large, the following generalized shape estimation technique is applied.

Figure pat00017

Here, i is an index that indicates the number of peaks in the data map, and separate the region as l n = 2n + 1.

When the distance of the echo signal is long and the signal size is small, the following generalized shape estimation technique is applied.

Figure pat00018

Figure pat00019

Here, i denotes the number of peaks in the data map, and ln = 2n + 1 denotes an index

Figure pat00020
)ego,
Figure pat00021
silver
Figure pat00022
or
Figure pat00023
.

It estimates the shape of the signal by calculating the slope of the median value and the dispersion value between the adjacent areas in the data map due to the distance of the fixed target in the water and the reflection signal characteristic according to various marine environment changes.

The fixed target clutter determiner 243 classifies the target signal into clutter signals using a linear classifier, and removes clutter signals. The threshold value is applied to the shape estimation result calculated in the shape estimation, and if the target value is above the threshold value, the target is classified as the clutter if it is below the threshold value. The threshold value is different depending on the type of the active ping such as CW (Continuous Wave) and FM (Frequency Modulation).

5 is a flowchart illustrating a process of applying a variable data map and variable statistical feature information for underwater fixed target and clutter identification according to an embodiment of the present invention. Referring to FIG. 5, a receiving unit (100 in FIG. 1) receives a data signal generated from a sonar (not shown) (step S510).

Thereafter, the signal processing unit (200 in FIG. 1) prepares the received data signal and generates a detection result to detect the target (steps S520 and S530).

When the detection result is generated, the signal processing unit 200 determines the size of the data map and sets a variable data map (step S540).

Once the variable data map is set, the variable statistical feature information is determined based on the variable data map and post-processed (step S550).

The fixed target tracking unit (300 in FIG. 1) tracks the fixed target using the detection data from which the clutter is removed and generates a tracking result (step S560).

Finally, the screen processing unit (400 in FIG. 1) displays the tracking result and / or the detection result (step S570).

100: Receiver 200: Signal processor
300: fixed target tracking unit 400:
210: preprocessing unit 220: target detection unit
230: Data map discrimination unit 231: Peak signal search unit
232: distance discrimination unit 233: signal size discrimination unit
234: Data Map Decision Unit 240: Fixed Target Postprocessing Unit
241: fixed target specific information extracting unit
242: fixed target shape estimating unit
243: fixed target clutter determiner

Claims (10)

A receiver for receiving a data signal generated from the sonar;
A signal processor for detecting a target by pre-processing the received data signal, determining a variable data map and variable statistical characteristic information according to a detection distance and a signal magnitude of the detected data, and post-processing the processed data;
A fixed target tracking unit for tracking and tracking the fixed target using clutter-free detection data; And
A screen processing unit for displaying the tracking result and the detection result;
And a variable statistical feature information generating unit for generating the variable statistical feature information based on the variable statistical feature information.
The method according to claim 1,
The signal processing unit,
A preprocessor for limiting the received data signal to a specific range using a preprocessing filter and generating preprocessed signal processing data;
A target detection unit for detecting a target from the signal processing data to generate detection data;
A data map determining unit for determining a data map size by extracting a distance and a signal size from the detected data and setting a variable data map; And
And a fixed target post-processor for extracting the variable statistical feature information based on the set variable data map and removing the clit signal using the variable statistical feature information. Applied device.
3. The method of claim 2,
The data map determining unit may determine,
A peak signal search unit for extracting a distance and a signal size of the echo signal by scanning a peak having a center value larger than a peripheral value in a specific region from the detected data;
A distance determination unit for determining a distance of the extracted echo signal;
A signal size discrimination unit for discriminating the extracted signal size; And
And a data map determining unit configured to determine a data map according to a distance of the discriminated echo signal and a discriminated signal size.
The method according to claim 1,
Wherein the variable statistical feature information includes a distance of a fixed target in the water and a reflection signal characteristic according to a marine environment change.
3. The method of claim 2,
Wherein the fixed target post-
A fixed target feature information extracting unit for extracting a median value and a variance value based on the data map;
A fixed target type lettuce which generates a shape estimation result by estimating a shape of a signal by combining the median value and the variance value according to a distance and a signal size of the extracted echo signal; And
And a fixed target clutter determiner for classifying the shape estimation result into a target signal and a clutter signal using a linear classifier and removing the clutter signal. .
6. The method of claim 5,
Wherein the shape estimation result is calculated by calculating a variance value for each region in the variable data map when the distance of the echo signal is close to and the magnitude is large. 6. The method of claim 5,
Wherein the shape estimation result is obtained by calculating a median slope, a dispersion value slope, and a variance value of a region of interest in the data map, when the distance of the echo signal is long and the size is small, in the variable data map A device for applying a variable data map and variable statistical feature information.
8. The method of claim 7,
The median value slope, the dispersion value slope, and the variance value are respectively expressed by the following equations
Figure pat00024
(here,
Figure pat00025
silver
Figure pat00026
The median value of the equation
Figure pat00027
(here,
Figure pat00028
silver
Figure pat00029
And the covariance value of the equation
Figure pat00030
(Wherein, the i is the number of peaks in the data map, l n = 2 < n + 1 >
Figure pat00031
)ego,
Figure pat00032
silver
Figure pat00033
or
Figure pat00034
The variable data map and the variable statistical feature information are calculated using the variable data map and the variable statistical feature information.
6. The method of claim 5,
Wherein the classification of the clutter signal and the target signal is a target signal if the threshold value is greater than a threshold value by applying a predetermined threshold to the shape estimation result and is classified as a clutter signal if the threshold value is less than the threshold value, Wherein the variable data map and the variable statistical feature information are applied differently depending on the type of the data.
Receiving a data signal generated by the receiver from the sonar;
The signal processing unit preprocessing the received data signal to generate a result of detecting the target;
A post-processing step of the signal processing unit determining the variable data map and the variable statistical feature information according to the detection distance and the signal amplitude of the peak signal based on the detection result and removing the clutter;
Tracking the fixed target using the detection data of the fixed target tracking unit clutter removed and generating the tracking result; And
The screen processing unit displaying the detection result and the tracking result;
And applying the variable data map and the variable statistical feature information.
KR1020160001252A 2016-01-05 2016-01-05 Clutter elimination Method and Apparatus for applying variable data map and variable statistic characteristics information for identifying underwater fixed target and clutter KR101813357B1 (en)

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Cited By (2)

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Publication number Priority date Publication date Assignee Title
KR20200041029A (en) * 2018-10-11 2020-04-21 국방과학연구소 Apparatus and method for recognizing underwater target
KR102544348B1 (en) 2022-06-22 2023-06-16 한화시스템 주식회사 Apparatus and method for generating training data for identifying underwater targets

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JP2951135B2 (en) * 1992-11-30 1999-09-20 三星電子株式会社 Pulse radar clutter remover
KR101497557B1 (en) * 2013-10-30 2015-03-02 국방과학연구소 Single-ping-clutter removing technique of active-sonar using estimation of multidimensional-feature-vector

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20200041029A (en) * 2018-10-11 2020-04-21 국방과학연구소 Apparatus and method for recognizing underwater target
KR102544348B1 (en) 2022-06-22 2023-06-16 한화시스템 주식회사 Apparatus and method for generating training data for identifying underwater targets

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