CN109655834B - Multi-beam sonar sounding method and system based on constant false alarm detection - Google Patents

Abstract

The invention relates to a multi-beam sonar sounding method and system based on constant false alarm detection. The multi-beam sonar sounding method based on constant false alarm detection of the present invention comprises the following steps: S1, transmitting a multi-beam sounding sonar beam, receiving a signal to be detected comprising a noise signal and a target echo signal of a target to be measured; S2, Pre-detect the signal to be detected by VI-CFAR, to obtain the echo time interval whose amplitude is greater than the first threshold in the signal to be detected; S3, sequentially obtain the time interval of the continuous echo time interval, when the time interval is less than the second threshold , merging the echo time intervals to finally obtain the complete echo time interval of the detection target; S4, obtaining the precise position of the detection target through the bottom detection method. The implementation of the invention can improve the detection effectiveness and stability, and can realize accurate detection of multiple targets.

Description

Multi-beam sonar sounding method and system based on constant false alarm detection

technical field

The present invention relates to the technical field of multi-beam sonar sounding, more specifically, to a multi-beam sonar sounding method and system based on constant false alarm detection.

Background technique

Multi-beam sounding sonar widely uses Mills cross-array technology to complete the acquisition of beam signals in multiple directions through transmitting and receiving beamforming technology. And through the bottom detection algorithm, it can measure dozens to hundreds of depth values at a time, and is widely used in underwater terrain surveying and mapping. The bottom detection algorithm is a linkage process of detection and estimation. Detection is to determine whether the sea bottom exists in the received echo signal. Estimation is to accurately estimate the time of arrival TOA and angle of arrival DOA of the sea bottom terrain on the basis of the detection results, and combine the known speed of sound to determine the Depth detection of seabed topography. Nowadays, traditional bottom detection technologies, such as WMT, energy center convergence method, split sub-array method and multi-sub-array method, etc., usually can only detect water objects and seabed topography, and cannot meet the needs of complex marine environments. Mapping needs. In order to ensure the reliable bottom detection ability of multi-beam bathymetric sonar and improve its detection ability of water body target position, a pre-detection link can be added before bottom detection to obtain the echo interval of water body target and sea bottom in advance, and then pass bottom detection The algorithm obtains accurate water body target position and seabed terrain depth at the same time.

The existing pre-detection method based on a fixed threshold is affected by the uneven background noise, and the detection stability and effectiveness need to be improved. The CFAR (Constant False Alarm Rate) detector calculates the detection threshold based on the background noise estimation unit, and the threshold is adaptively adjusted with background fluctuations, maintaining a constant false alarm probability, and is widely used in radar and sonar signal detection. Existing CFAR detection methods, such as cell-average CFAR (CA-CFAR) detectors, ordered statistical CFAR (OS-CFAR) detectors, and automatically deleted average CFAR (CCA-CFAR) detectors, etc., usually operate on a class-specific It has a better detection performance in the environment, but there is a larger detection loss in the other environments. In addition, due to the fluctuation and broadening of multi-beam bathymetric sonar echoes, the detection results of target echoes may be discrete, which cannot be effectively used in multi-beam bathymetric sonar bottom detection algorithms.

Contents of the invention

The technical problem to be solved by the present invention is to provide a multi-beam sonar sounding method and system based on constant false alarm detection in view of the above-mentioned partial technical defects of the prior art.

The technical solution adopted by the present invention to solve its technical problems is: construct a kind of multi-beam sonar sounding method based on constant false alarm detection, comprising the following steps:

S1. Transmitting multi-beam sounding sonar beams, receiving signals to be detected including noise signals and target echo signals of the target to be measured;

S2. Perform pre-detection on the signal to be detected by VI-CFAR, so as to obtain an echo time interval whose amplitude is greater than a first threshold in the signal to be detected;

S3. Acquire time intervals of consecutive echo time intervals in sequence, and when the time intervals are smaller than a second threshold, combine the echo time intervals to finally obtain a complete echo time interval of the detection target;

S4. Obtain the precise position of the detection target by using a bottom detection method.

Preferably, the detection target includes a plurality of detection targets, and the second threshold includes a plurality of second thresholds respectively corresponding to the plurality of detection targets;

In the step S3, the merging of the echo time intervals to obtain the complete echo time interval of the detection target includes:

Complete echo time intervals corresponding to the multiple detection targets are respectively obtained according to the multiple second thresholds.

Preferably, the method also includes:

S3-1. Obtain a beam footprint of the detection target to obtain a predicted time width of the detection target, and obtain the second threshold according to the predicted time width.

Preferably, the calculation method of the predicted time width is:

Wherein, θ is the incident angle of the sonar beam, t is the round-trip time of the sonar beam, and θ is the -3dB beamwidth of the sonar beam.

Preferably, the obtaining the beam footprint of the detection target includes: obtaining the beam footprint corresponding to the detection target in two consecutive echo time intervals.

Preferably, in the step S1, the receiving the signal to be detected including the noise signal and the target echo signal of the target to be tested includes:

The noise signal and the target echo signal of the target to be measured are received and subjected to receiving beamforming and wave detection to obtain the signal to be detected.

Preferably, in the step S2, the pre-detection of the signal to be detected by VI-CFAR includes:

Obtain the variability index VI in the detection sliding window, and judge whether the target to be measured is a uniform environment according to the variability index VI;

When it is a uniform environment, pre-detect the signal to be detected by CA-CFAR;

When the environment is non-uniform, the signal to be detected is pre-detected by CCA-CFAR.

Preferably, said obtaining the variability index VI in the detection sliding window comprises:

Obtain the variability index VI of the front sliding window and the trailing sliding window of the detection sliding window respectively;

The method also includes:

Comparing the variability index VI with a third set threshold respectively to confirm whether the front sliding window and the trailing sliding window are uniform sliding windows;

When any one of the front sliding window and the trailing sliding window is a uniform sliding window, pre-detecting the signal to be detected through the CA-CFAR based on the uniform sliding window;

When both the front sliding window and the trailing sliding window are uniform sliding windows, pre-detecting the signal to be detected through the CCA-CFAR based on the entire sliding window;

When both the leading sliding window and the trailing sliding window are non-uniform sliding windows, the signal to be detected is pre-detected by using the CCA-CFAR based on the entire sliding window.

Preferably, in the step S4, the bottom detection method includes any one of WMT, split sub-array method and multi-sub-array method.

The present invention also constructs a multi-beam sonar sounding device based on constant false alarm detection, including:

The sonar transmitting unit is used to transmit the multi-beam depth sounding sonar beam;

a sonar receiving unit, configured to receive signals to be detected including noise signals and target echo signals of the target to be measured;

A signal processing unit, configured to process the signal to be detected according to any one of the methods above.

The implementation of the constant false alarm detection-based multi-beam sonar sounding method and system of the present invention has the following beneficial effects: the detection effectiveness and stability are improved, and accurate detection of multiple targets can be realized.

Description of drawings

The present invention will be further described below in conjunction with accompanying drawing and embodiment, in the accompanying drawing:

Fig. 1 is the program flowchart of an embodiment of the multi-beam sonar sounding method based on constant false alarm detection of the present invention;

Fig. 2 is a schematic diagram of the echo time interval;

Fig. 3 is a schematic diagram of the echo time interval of the water target and the seabed;

Fig. 4 is the program flowchart of another embodiment of the multi-beam sonar sounding method based on constant false alarm detection of the present invention;

Figure 5 is a schematic diagram of irradiation based on beam footprints;

Fig. 6 is a comparison diagram of the detection results of the present invention and the prior art;

Fig. 7 is the schematic diagram of detection result of the present invention;

Fig. 8 is a logic block diagram of an embodiment of the multi-beam sonar sounding system based on constant false alarm detection in the present invention.

Detailed ways

In order to have a clearer understanding of the technical features, purposes and effects of the present invention, the specific implementation manners of the present invention will now be described in detail with reference to the accompanying drawings.

As shown in Figure 1, in an embodiment of the multi-beam sonar sounding method based on constant false alarm detection of the present invention, comprise the following steps:

S1. Transmit multi-beam sounding sonar beams, and receive signals to be detected including noise signals and target echo signals of targets to be measured; specifically, during underwater terrain detection, transmit multi-beam sounding sonar beams through a transmitting array, the After the sonar beam is refracted by seawater and reflected by the seabed or intermediate objects in the water, it is received by the receiving array. The received signal will be used as the signal to be detected after beam forming and detection. The signal to be detected here is included in the The target echo signal reflected by the target to be measured also includes noise signals caused by environmental influences.

S2. Pre-detect the signal to be detected by VI-CFAR, so as to obtain the echo time interval whose amplitude is greater than the first threshold in the signal to be detected; specifically, in the pre-detection process of VI-CFAR, according to the threshold of VI-CFAR, which is the first threshold A threshold extracts echo time intervals whose amplitudes are greater than the first threshold in the signal to be detected, and obtains several discrete echo time intervals related to the target to be measured. As shown in Fig. 2, two time intervals (t1, t2) and (t3, t4) are obtained.

S3. Acquire the time intervals of consecutive echo time intervals in sequence, and when the time interval is less than the second threshold, combine the echo time intervals to finally obtain the complete echo time interval of the detection target; specifically, compare adjacent echoes The time interval of the time interval, when the time interval between the two echo time intervals is relatively small and meets certain requirements, that is, when the second threshold is met, it can be considered that the two echo time intervals come from the same target to be measured, and the two echo time intervals can be combined The echo time intervals are merged. Here, continuous comparison is performed, and the echo time intervals that meet the requirements are combined, so that the complete echo interval of the target to be measured can be obtained. Here, when the time interval between adjacent echo time intervals is equal to or exceeds the second threshold, it can be considered that the two echo time intervals do not come from the same target to be measured, and the two echo time intervals are processed separately. In the embodiment shown in Figure 2, the difference between the threshold and t3-t2 is compared, and when the difference meets the threshold requirement, (t1, t2) and (t3, t4) can be combined to obtain a Complete echo time interval (t1, t4). With more echo time intervals, successive merging is possible.

S4. Acquiring the precise position of the detection target through the bottom detection method. Specifically, after obtaining the complete echo time interval of the target to be measured, on the obtained complete echo time interval of the target to be measured, use the bottom detection algorithm to accurately estimate the angle of arrival DOA and time of arrival of the sonar beam to the target to be measured TOA, combined with the known speed of sound to obtain the precise position of the target to be measured.

Further, the detection target includes a plurality of detection targets, and the second threshold includes a plurality of second thresholds respectively corresponding to the plurality of detection targets; in step S3, combining echo time intervals to obtain a complete echo time interval of the detection target includes : Obtain the complete echo time intervals corresponding to the multiple detection targets according to the multiple second thresholds. Specifically, as shown in Figure 3, the common seabed detection includes seabed terrain detection and the detection of water objects in the middle of the sea, where the pre-detection results of the water body object and the seabed are respectively obtained, and the discrete pre-detection results that meet the requirements are combined. In a continuous time interval, the complete echo time intervals of the water target and the seabed can be obtained respectively. A in the figure corresponds to the water body target, and B in the figure corresponds to the seabed, so that the water body target and the seabed can be accurately calculated separately without mutual interference.

Preferably, as shown in Figure 4, the multi-beam sonar sounding method based on constant false alarm detection of the present invention also includes:

S3-1. Obtain the beam footprint of the detection target to obtain the predicted time width of the detected target, and obtain a second threshold according to the predicted time width. Specifically, the calculation method of the second threshold here may obtain the predicted time width of the detected target by detecting the beam footprint of the target, and obtain the second threshold according to the predicted time width. The predicted time width reflects the broadening of the water target or the seabed acoustic echo (because the acoustic beam illuminates the target on a surface, not a point, the target echo will widen). When the interval of discrete time intervals is within this range, it means that these discrete echoes come from the same target.

Further, the calculation method of the predicted time width is:

Among them, θ is the incident angle of the sonar beam, t is the round-trip time of the sonar beam, and Θ is the -3dB beamwidth of the sonar beam. Specifically, since the beam has a certain beam width Θ, the arrival time of the target echo at different positions under each beam footprint is different, as shown in Figure 5, the return time of the echo at point A in the beam footprint is the shortest and point B is the longest , so that the target echo signal in each beam has a certain spread in time. Assuming that the irradiation of the beam footprint on the target in the water body and the seabed is horizontal, the width of the echo of the water body target and the seabed in time can be approximated by the above formula.

Further, acquiring the beam footprint of the detection target includes: acquiring beam footprints corresponding to the detection target in two consecutive echo time intervals. Specifically, the beam footprint should correspond to the two time intervals that need to be compared for merging. It can also be understood as taking the start time of the two merging time intervals to start obtaining the beam footprint. For example, in Figure 2, the echo time The interval (t1, t2) is compared with (t3, t4) to determine whether to merge, then take its starting time t1 to calculate according to the calculation method of the above-mentioned predicted time width, and obtain its corresponding second threshold value, when the echo When the time interval changes, the time in the prediction time width calculation here also changes accordingly, thus realizing dynamic threshold setting.

Further, in step S1, receiving the signal to be detected including the noise signal and the target echo signal of the target to be measured includes: receiving the noise signal and the target echo signal of the target to be measured through receiving beamforming and detection to obtain the signal to be detected Signal. Specifically, the received noise signal and the target echo signal of the target to be detected are detected to obtain the required signal to be detected. The detection method here may be envelope detection or square rate detection.

Further, in step S2, the pre-detection of the signal to be detected through VI-CFAR includes: obtaining the variability index VI in the detection sliding window, and judging whether the target to be tested is a uniform environment according to the variability index VI; when it is a uniform environment , the signal to be detected is pre-detected through CA-CFAR; when it is a non-uniform environment, the signal to be detected is pre-detected through CCA-CFAR. Specifically, the process of detecting the signal to be detected includes calculating the variability index VI within the detection sliding window:

为对应滑窗的均值，n为对应滑窗的长度。然后通过比较VI与设定阈值K_VI的大小，判断滑窗是否均匀，判断方法如下：where X is the sliding window data,

is the mean value of the corresponding sliding window, and n is the length of the corresponding sliding window. Then, by comparing the size of VI and the set threshold K _VI , it is judged whether the sliding window is uniform. The judgment method is as follows:

The VI-CFAR detector selects different CFAR detectors according to whether the sliding window is uniform or not. For a uniform environment, the CA-CFAR detector has the best detection performance; at this time, the VI-CFAR detector chooses the sliding window as the unit of background noise estimation, and uses the CA-CFAR detector for detection. For the non-uniform case, the VI-CFAR detector chooses CCA-CFAR at this time to improve the detection performance of the detector when there is unknown interference in the sliding window, while maintaining the detection performance of the detector in other cases.

Further, obtaining the variability index VI in the detection sliding window includes: respectively obtaining the variability index VI of the front sliding window and the trailing sliding window of the detection sliding window; the method also includes: respectively comparing the variability index VI with the third setting Threshold to confirm whether the front sliding window and the trailing sliding window are uniform sliding windows; when any of the leading sliding windows and trailing sliding windows is a uniform sliding window, pre-detect the signal to be detected through CA-CFAR based on the uniform sliding window ; When both the front sliding window and the trailing sliding window are uniform sliding windows, pre-detect the signal to be detected based on the entire sliding window through CCA-CFAR; when the leading sliding window and the trailing sliding window are both non-uniform sliding windows, Pre-detect the signal to be detected by CCA-CFAR based on the entire sliding window. Specifically, when calculating the variability index VI in the detection sliding window, the front sliding window and the trailing sliding window of the detection sliding window can be calculated separately, and the front sliding window and the trailing sliding window can be judged respectively. When the trailing sliding windows are uniform, the CA-CFAR detector has the best detection performance; the VI-CFAR detector selects all sliding windows as the unit of background noise estimation, and uses the CA-CFAR detector for detection. For the case where one of the front and back sliding windows is uniform and the other is non-uniform, the VI-CFAR detector selects a uniform sliding window as the unit for background noise estimation, and uses the CA-CFAR detector for detection to improve this situation. Lower detector performance. For the case of target interference in both leading and trailing sliding windows, the VI-CFAR detector uses CCA-CFAR.

Further, in step S4, the bottom detection method includes any one of WMT, split sub-array method and multi-sub-array method. Specifically, based on the obtained echo time interval of the target to be measured, conventional bottom detection algorithms, such as WMT, split sub-array method and multi-subarray method, etc. are used to obtain accurate time-of-arrival estimation t and angle-of-arrival estimation θ, and combined with the Know the speed of sound c and the formula:

Further determine the precise position of the target to be measured, such as the water body target and the seabed, and realize the simultaneous detection of the water body target and the seabed topography. However, the traditional bottom detection algorithm can only retain one measurement result of the water target and the seabed. The bottom detection method commonly used here is not limited to the above examples.

Combined with Fig. 6, (a) takes WMT as an example to detect the measured data of multi-beam bathymetric sonar. The traditional WMT bottom detection method only detects the bottom topography. And (b) according to the detection result obtained by the multi-beam sonar sounding method based on constant false alarm detection of the present invention, when the seabed topography B is detected, the target position in the water body is also detected, that is, the water body target B, which improves the multi-beam sounding method. Deep sonar detection capabilities. Refer to FIG. 7 for the multi-beam sounding sonar water body imaging diagram obtained according to the present invention.

In addition, as shown in Figure 8, a multi-beam sonar sounding device based on constant false alarm detection of the present invention includes:

The sonar transmitting unit is used to transmit the multi-beam depth sounding sonar beam;

a sonar receiving unit, configured to receive signals to be detected including noise signals and target echo signals of the target to be measured;

A signal processing unit, configured to process the signal to be detected according to any one of the methods above. Specifically, for the mutual cooperation and work among the units of the multi-beam sonar sounding device based on constant false alarm detection, refer to the above method, which will not be repeated here.

It can be understood that the above examples only express the preferred implementation of the present invention, and its description is relatively specific and detailed, but it should not be interpreted as limiting the patent scope of the present invention; it should be pointed out that for those of ordinary skill in the art In other words, on the premise of not departing from the concept of the present invention, the above-mentioned technical features can be freely combined, and some modifications and improvements can also be made, all of which belong to the protection scope of the present invention; All equivalent transformations and modifications should fall within the scope of the claims of the present invention.

Claims (8)

1. A multi-beam sonar sounding method based on constant false alarm detection is characterized by comprising the following steps:

s1, emitting a multi-beam sounding sonar beam, and receiving a signal to be detected comprising a noise signal and a target echo signal of a target to be detected;

s2, pre-detecting the signal to be detected through VI-CFAR to obtain an echo time interval with the amplitude larger than a first threshold value in the signal to be detected;

s3, sequentially obtaining time intervals of continuous echo time intervals, and combining the echo time intervals when the time intervals are smaller than a second threshold value so as to finally obtain a complete echo time interval of the target to be detected;

s4, acquiring the accurate position of the target to be detected through a bottom detection method;

the method further comprises the following steps:

s3-1, obtaining a beam footprint of the target to be detected to obtain a pre-judgment time width of the target to be detected, and obtaining the second threshold according to the pre-judgment time width;

the calculation method of the prejudgment time width comprises the following steps:

wherein θ is the incident angle of the sonar beam, t is the round trip time of the sonar beam, and Θ is the-3 dB beam width of the sonar beam.

2. The constant false alarm detection-based multi-beam sonar depth sounding method according to claim 1, wherein the target to be measured includes a plurality of targets to be measured, and the second threshold includes a plurality of second thresholds respectively corresponding to the plurality of targets to be measured;

in step S3, the merging the echo time intervals to obtain a complete echo time interval of the target to be measured includes:

and respectively obtaining complete echo time intervals corresponding to the multiple targets to be detected according to the multiple second threshold values.

3. The constant false alarm detection-based multi-beam sonar depth sounding method according to claim 1, wherein the obtaining of the beam footprint of the target to be measured includes: and acquiring beam footprints corresponding to the target to be detected in two continuous echo time intervals.

4. The multi-beam sonar depth sounding method based on constant false alarm detection according to claim 1, wherein in step S1, the receiving a signal to be detected including a noise signal and a target echo signal of a target to be detected includes:

and receiving the noise signal and a target echo signal of the target to be detected, and forming and detecting through a receiving beam to obtain the signal to be detected.

5. The constant false alarm detection-based multi-beam sonar depth sounding method according to claim 1, wherein in step S2, the pre-detecting the signal to be detected by VI-CFAR comprises:

acquiring a variability index VI in a detection sliding window, and judging whether the target to be detected is a uniform environment or not according to the variability index VI;

when the environment is uniform, pre-detecting the signal to be detected through CA-CFAR;

and when the environment is non-uniform, pre-detecting the signal to be detected through CCA-CFAR.

6. The constant false alarm detection-based multi-beam sonar sounding method according to claim 5, wherein the obtaining a variability index VI within a detection sliding window comprises:

respectively obtaining the variability indexes VI of the front edge sliding window and the rear edge sliding window of the detection sliding window;

the method further comprises the following steps:

respectively comparing the variability index VI with a third set threshold value to determine whether the leading edge sliding window and the trailing edge sliding window are uniform sliding windows;

when any one of the front edge sliding window and the back edge sliding window is a uniform sliding window, pre-detecting the signal to be detected through the CA-CFAR based on the uniform sliding window;

when the front edge sliding window and the back edge sliding window are both uniform sliding windows, pre-detecting the signal to be detected through the CCA-CFAR based on the whole sliding window;

and when the front edge sliding window and the back edge sliding window are both non-uniform sliding windows, pre-detecting the signal to be detected through the CCA-CFAR based on the whole sliding window.

7. The constant false alarm detection-based multi-beam sonar sounding method according to claim 1, wherein in step S4, the bottom detection method includes any one of WMT, a split sub-array method, and a multi-sub-array method.

8. The utility model provides a multi-beam sonar sounding device based on constant false alarm detects which characterized in that includes:

the sonar emission unit is used for emitting multi-beam sounding sonar beams;

the sonar receiving unit is used for receiving a signal to be detected comprising a noise signal and a target echo signal of a target to be detected;

signal processing unit for processing the signal to be detected according to the method of any of claims 1 to 7.

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