Distance measuring device and distance measuring method

Abstract

To provide a ranging device and a ranging method capable of obtaining distance to a target regardless of an error of an observed azimuth.SOLUTION: A ranging device acquires distance information regarding distance to a target on the basis of a signal from the target received by multiple receiver arrays, and includes a phase-adjusting processing portion for performing phase-adjusting processing of signals for each receiver array, an azimuth calculation portion for calculating a target azimuth as an azimuth in which a target exists on the basis of a result of phase-adjusting processing for each receiver array, a standard deviation calculation portion for calculating a standard deviation of a target azimuth for each receiver array, a probability density calculation portion for calculating probability density of a position of a target relative to a ranging base point on the basis of a target azimuth and a standard deviation for each receiver array, a simultaneous probability density calculation portion for calculating simultaneous probability density by multiplying probability density of multiple receiver arrays, and an output portion for outputting, as the distance information, one of the simultaneous probability density, and distance to a target from a ranging base point acquired based on the simultaneous probability density.SELECTED DRAWING: Figure 11

Description

[Technical Field]

[0001] The present invention relates to a distance measuring device and a distance measuring method for measuring the distance to a target in a passive sonar. [Background technology]

[0002] Conventionally, passive sonars are known for detecting sound waves emitted by moving objects such as ships and marine life in the sea and lakes to estimate their positions (for example, Patent Document 1). One method for measuring the distance to a target in a passive sonar is to calculate the distance using the principle of triangulation, using the direction of the target signal observed by two receiver arrays. [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] Patent No. 6236755 [Overview of the Initiative] [Problems that the invention aims to solve]

[0004] Generally, passive sonars calculate the direction by detecting the target signal buried in background noise, so the observed direction contains an error compared to the true target direction. Therefore, since the distance is calculated using the direction containing the error, the calculated distance will also contain an error. In this case, depending on the error, there is a problem in that the distance cannot be calculated using the conventional principle of triangulation.

[0005] The present invention is based on the above-mentioned problems and aims to provide a distance measuring device and method that can determine the distance to a target regardless of the error in the observed direction. [Means for solving the problem]

[0006] The distance measuring device according to the present invention is a distance measuring device that acquires distance information relating to the distance to a target based on signals from a target received by a plurality of receiver arrays, and comprises a phase aligning processing unit that performs phase aligning processing on the signals for each receiver array, a direction calculation unit that calculates the target direction, which is the direction in which the target is located, based on the result of the phase aligning processing for each receiver array, a standard deviation calculation unit that calculates the standard deviation of the target direction for each receiver array, and a unit that calculates the target direction and standard deviation for each receiver array The probability density of the distance from the receiver array to the location where the target exists, and The system comprises: a probability density calculation unit that calculates the probability density of the target's position relative to the distance measurement base point based on the above; a simultaneous probability density calculation unit that calculates the simultaneous probability density by multiplying the probability densities of multiple receiver arrays; and an output unit that outputs at least one of the simultaneous probability density or the distance from the distance measurement base point to the target obtained based on the simultaneous probability density as distance information. The probability density of the distance from the receiver array to the location where the target exists is the probability density assuming that the target exists with equal probability up to a certain distance from the receiver array.

[0007] Furthermore, the distance measurement method according to the present invention is a distance measurement method performed by a distance measuring device that acquires distance information relating to the distance to a target based on signals from a target received by a plurality of receiver arrays, comprising the steps of: performing phase alignment processing on the signals for each receiver array; calculating the target direction, which is the direction in which the target is located, based on the results of the phase alignment processing for each receiver array; calculating the standard deviation of the target direction for each receiver array; and calculating the target direction and standard deviation for each receiver array. The probability density of the distance from the receiver array to the location where the target exists, and The process includes the steps of: calculating the probability density of the target's position relative to the distance measurement base point based on the above; calculating the simultaneous probability density by multiplying the probability densities of multiple receiver arrays; and outputting at least one of the simultaneous probability density or the distance from the distance measurement base point to the target obtained based on the simultaneous probability density as distance information. Furthermore, the probability density of the distance from the receiver array to the location where the target exists is the probability density assuming that the target exists with equal probability up to a certain distance from the receiver array. [Effects of the Invention]

[0008] According to the distance measuring device and distance measuring method of the present invention, the distance to a target can be determined regardless of the error in the observed direction by calculating the simultaneous probability density based on the signals of multiple receiver arrays and outputting the distance to the target based on the simultaneous probability density. Furthermore, by outputting the simultaneous probability density calculated based on the signals of multiple receiver arrays, the distance to the target can be determined based on the value of the simultaneous probability density, regardless of the error in the observed direction. [Brief explanation of the drawing]

[0009] [Figure 1] This is an example of a probability density f1(θ'1). [Figure 2] This is an example of a probability density f1(r'1). [Figure 3] This is an example of a probability density f1(θ'1,r'1). [Figure 4] This is an example of a probability density f²(θ'²). [Figure 5] This is an example of a probability density f²(r'²). [Figure 6] This is an example of a probability density f²(θ'²,r'²). [Figure 7] This is a geometrical diagram of the receiver array S1, receiver array S2, and the distance measurement base point. [Figure 8] This is an example of a probability density f1r(θ'r,r'r). [Figure 9] This is an example of a probability density f2r(θ'r,r'r). [Figure 10] This is an example of a joint probability density fr(θ'r,r'r). [Figure 11] This is a schematic diagram of the distance measuring device 100 according to Embodiment 1. [Figure 12] This is an example of how the joint probability density fr(θ'r,r'r) can be represented using grayscale. [Figure 13] This is a diagram illustrating the principle of a conventional distance measurement method. [Figure 14] This is a schematic diagram of a conventional distance measuring device 10. [Figure 15] This figure shows the problems with conventional distance measurement methods. [Figure 16] This figure shows the problems with conventional distance measurement methods. [Figure 17] This is an example of the probability density f1r(θ'r,r'r) when the conditions of equation (17) are met. [Figure 18] This is an example of the probability density f2r(θ'r,r'r) when the conditions of equation (17) are met. [Figure 19] This is an example of the joint probability density fr(θ'r,r'r) when the conditions of equation (17) are met. [Figure 20] Figure 19 shows an example of the simultaneous probability density display. [Figure 21] This diagram illustrates the method for calculating distance using the distance acquisition unit in a modified example. [Modes for carrying out the invention]

[0010] Before describing the embodiments, the principle of the present invention will be explained. In the following, the passive sonar will be described as having two receiver arrays S1 and S2 located at separate locations. The standard deviation of the target azimuth θm1 observed by receiver array S1 is σ θ1 Let's assume that the probability density f1(θ'1) of the target being at direction θ'1 when the target direction θm1 is observed is given by equation (1).

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[0011] Figure 1 shows an example of the probability density f1(θ'1). On the other hand, distance information to the target cannot be obtained from observations using the receiver array S1. Therefore, assuming that the maximum distance at which the receiver array S1 can detect the target signal is rmax1, and assuming that the target exists with the same probability in the range from distance 0 to rmax1, the probability density f1(r'1) for the target to be at distance r'1 is given by equation (2).

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[0012] Figure 2 shows an example of a probability density f1(r'1). From equations (1) and (2), the probability density f1(θ'1,r'1) of the target being at position (θ'1,r'1) is given by equation (3).

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[0013] Figure 3 shows an example of a probability density f1(θ'1,r'1). In this example of a two-dimensional probability density as shown in Figure 3, black represents a low probability density and white represents a high probability density.

[0014] The standard deviation of the target azimuth θm2 observed by the receiver array S2 is σ θ2 Let rmax2 be the maximum distance at which the receiver array S2 can detect the target signal. Similar to the case of receiver array S1, the probability density f2(θ'2,r'2) of the target being at position (θ'2,r'2) is given by equation (4).

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[0015] Figure 4 shows an example of the probability density f²(θ'²), Figure 5 shows an example of the probability density f²(r'²), and Figure 6 shows an example of the probability density f²(θ'²,r'²).

[0016] Next, we consider the probability density when the target signal is observed by receiver array S1 and receiver array S2 using equations (3) and (4). Since receiver array S1 and receiver array S2 observe signals from different base points, we first convert equations (3) and (4) into probability densities for the target position from a common base point. Figure 7 is a geometrical arrangement diagram of receiver array S1, receiver array S2, and the distance measurement base point. Here, the "distance measurement base point" is the common base point for receiver array S1 and receiver array S2.

[0017] In Figure 7, baseline l BLet the x-axis be, the receiver array S1 and the receiver array S2 are arranged on the x-axis. In xy coordinates, the coordinates of the receiver array S1 are (x1, 0), the coordinates of the receiver array S2 are (x2, 0), and the coordinates of the ranging base point are (x r , y r ). Consider an arbitrary position with an azimuth θ' r and a distance r' r from the ranging base point. The xy coordinates of this arbitrary position are (r' r cosθ' r +x r , r' r sinθ' r +y r ). When this arbitrary position is viewed from the receiver array S1, the azimuth θ'1 is represented by formula (5), and the distance r'1 is represented by formula (6). [Mathematical] [Mathematical]

[0018] Similarly, when this arbitrary position is viewed from the receiver array S2, the azimuth θ'2 is represented by formula (7), and the distance r'2 is represented by formula (8). [Mathematical] [Mathematical]

[0019] Next, the probability density f1(θ'1, r'1) when a target is observed by the receiver array S1 in formula (3) is converted into the probability density f 1r (θ' r , r' r ) from the ranging base point according to the following formula (9). FIG. 8 is an example of the probability density f 1r (θ' r , r' r ). Note that |J1| in formula (9) means the absolute value of the determinant J1. [Mathematical]

[0020] Here, J1 is represented by the following equation (10). Note that |A| in equation (10) represents the determinant of matrix A.

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[0021] Similarly, the probability density f2(θ'2,r'2) when the target is observed by the receiver array S2 in equation (4) is given by the probability density f from the distance measurement base point using the following equation (11). 2r (θ' r ,r' r Convert to (). Figure 9 shows the probability density f 2r (θ' r ,r' r This is an example of that.

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[0022] Here, J2 is expressed by the following equation (12).

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[0023] The probability density f when the target is observed by receiver array S1 and receiver array S2. r (θ' r ,r' r Assuming that each error is independent, the equation becomes (13). In the following explanation, the probability density f when the target is observed by receiver array S1 and receiver array S2 is used. r (θ' r ,r' r This is called the "joint probability density."

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[0024] Figure 10 shows the joint probability density f r (θ' r, r' rThis is an example of joint probability density f. r (θ' r ,r' r The position with the largest joint probability density f has the highest probability of being the target. r (θ' r ,r' r By calculating this, the distance to the target can be estimated.

[0025] Embodiment 1. Figure 11 is a schematic diagram of the distance measuring device 100 according to Embodiment 1. The distance measuring device 100 constitutes part of a passive sonar and is connected to two receiver arrays S1 and S2 via wired or wireless communication. The distance measuring device 100 measures the distance to a target based on signals from the two receiver arrays S1 and S2. Receiver array S1 and receiver array S2 each consist of multiple receivers. The distance measuring device 100 consists of a computing device such as a microcomputer or CPU that implements various functions by executing software, hardware such as circuit devices corresponding to various functions, or both.

[0026] As shown in Figure 11, the distance measuring device 100 includes input units 11 and 12, phase adjustment processing units 21 and 22, direction calculation units 31 and 32, standard deviation calculation units 41 and 42, probability density calculation units 51 and 52, simultaneous probability density calculation unit 6, distance acquisition unit 7, and output unit 8.

[0027] Input 11 is an input terminal to which the output signal from receiver array S1 is input, and input 12 is an input terminal to which the output signal from receiver array S2 is input. Phase shaping processing unit 21 performs phase shaping processing on the signal input from input 11, and phase shaping processing unit 22 performs phase shaping processing on the signal input from input 12.

[0028] The direction calculation unit 31 detects a target signal based on the phase adjustment processing result input from the phase adjustment processing unit 21 and calculates the target direction, which is the direction in which the target is located. The direction calculation unit 32 detects a target signal based on the phase adjustment processing result input from the phase adjustment processing unit 22 and calculates the target direction. The standard deviation calculation unit 41 calculates the standard deviation of the target direction input from the direction calculation unit 31, and the standard deviation calculation unit 42 calculates the standard deviation of the target direction input from the direction calculation unit 32.

[0029] The probability density calculation unit 51 calculates the probability density using the target direction input from the direction calculation unit 31 and the standard deviation of the target direction input from the standard deviation calculation unit 41. The probability density calculation unit 52 calculates the probability density using the target direction input from the direction calculation unit 32 and the standard deviation of the target direction input from the standard deviation calculation unit 42. The simultaneous probability density calculation unit 6 calculates the simultaneous probability density by multiplying the probability density input from the probability density calculation unit 51 and the probability density input from the probability density calculation unit 52.

[0030] The distance acquisition unit 7 acquires the distance from the distance measurement base point to the target based on the simultaneous probability density input from the simultaneous probability density calculation unit 6. The output unit 8 is an output terminal that outputs the distance acquired by the distance acquisition unit 7 to an external device or the like.

[0031] The operation of the distance measuring device 100 in this embodiment will now be described. The target signal received by the receiver array S1 is input to the input unit 11 and sent to the phase adjustment processing unit 21. The target signal received by the receiver array S2 is input to the input unit 12 and sent to the phase adjustment processing unit 22.

[0032] The phase adjustment processing unit 21 processes at time t k In this process, the target signal input from the input unit 11 is phase-aligned to form a beam with direction N1 for n=1 to N1, and the processing result P1 θ (k,n)(n=1~N1) is sent to the direction calculation unit 31. The phase adjustment processing unit 22 calculates the time t k In this process, the target signal input from the input unit 12 is phase-aligned to form a beam with direction N2 for n=1 to N2, and the processing result P2 θ(k,n)(n=1~N2) is sent to the direction calculation unit 32.

[0033] The direction calculation unit 31 processes the input phase adjustment result P1 θ The beam with the energy peak at (k,n) is detected, and the azimuth of the detected peak beam is calculated. The azimuth calculation unit 31 then calculates the target azimuth θm1(t k The result is sent to the standard deviation calculation unit 41 and also to the probability density calculation unit 51.

[0034] If the spacing of the phase-corrected beams is not sufficiently fine compared to the target azimuth error caused by background noise, then the phase-corrected result P1 θ By interpolating (k,n) in the azimuthal direction, the direction in which the energy peaks is estimated, and the target direction θm1(t k ) may also be used. As an estimation method, for example, the phase adjustment result P1 θ One method involves fitting a quadratic curve to three points: the beam azimuth and energy value at the peak point (k,n), and the azimuth and energy values ​​on both sides of that point. The azimuth at which the fitted quadratic curve peaks is then calculated. The peak azimuth estimated in this way is then used as the target azimuth θm1(t k It may also be used as ).

[0035] Target direction θm1(t k When the target bearing θm1(t) is sent to the standard deviation calculation unit 41, the standard deviation calculation unit 41 calculates the target bearing θm1(t k ) Standard deviation σ θ1 (t k The standard deviation σ is calculated and sent to the probability density calculation unit 51. θ1 (t k The target bearing is calculated, for example, using the target bearings of the past Q samples, by the following equation (14). The target bearings of the past Q samples are stored in a memory (not shown) provided by the distance measuring device 100.

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[0036] Here, the target bearing θm1(t kThe average value of ) is expressed by the following formula (15).

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[0037] Target bearing θm1(t) from bearing calculation unit 31 k ) and the standard deviation σ from the standard deviation calculation unit 41 θ1 (t k When the above equation (9) is sent to the probability density calculation unit 51, the probability density calculation unit 51 uses the above equation (9) to calculate the probability density f 1r (θ' r ,r' r The probability density calculation unit 51 then calculates the calculated probability density f. 1r (θ' r ,r' r The result is sent to the simultaneous probability density calculation unit 6.

[0038] The direction calculation unit 32 and the standard deviation calculation unit 42 perform the same operations as the direction calculation unit 31 and the standard deviation calculation unit 41, respectively, on the information based on the target signal received by the receiver array S2, and calculate the target direction θm2(t k ) and standard deviation σ θ2 (t k The target bearing θm²(t) from the bearing calculation unit 32 is calculated. k ) and the standard deviation σ from the standard deviation calculation unit 42 θ2 (t k When the above equation (11) is sent to the probability density calculation unit 52, the probability density calculation unit 52 uses the above equation (11) to calculate the probability density f 2r (θ' r ,r' r The probability density calculation unit 52 then calculates the calculated probability density f. 2r (θ' r ,r' r The result is sent to the simultaneous probability density calculation unit 6.

[0039] Probability density f from the probability density calculation unit 51 1r (θ' r ,r' r ) and the probability density f from the probability density calculation unit 52 2r (θ' r ,r'r ) are sent to the joint probability density calculation unit 6, the joint probability density calculation unit 6 calculates the joint probability density f r (θ' r ,r' r ) using the above-mentioned equation (13). Then, the joint probability density calculation unit 6 sends the calculated joint probability density f r (θ' r ,r' r ) to the distance acquisition unit 7.

[0040] The distance acquisition unit 7 acquires the distance from the ranging reference point to the target based on the joint probability density f r (θ' r ,r' r ) from the joint probability density calculation unit 6. For example, the distance acquisition unit 7 acquires the distance rm at the position where the joint probability density f r (θ' r ,r' r ) is maximized as the distance from the ranging reference point to the target. FIG. 12 is an example where the joint probability density f r (θ' r ,r' r ) is displayed in grayscale. As shown in FIG. 12, when the joint probability density f r (θ' r ,r' r ) is displayed in grayscale, the distance rm corresponding to the position closest to white is the target distance at which the joint probability density f r (θ' r ,r' r ) is maximized. The distance acquisition unit 7 sends the acquired distance rm to the output unit 8.

[0041] The output unit 8 outputs the distance rm from the distance acquisition unit 7 to an external device or the like. Note that the output unit 8 may output the joint probability density f r (θ' r ,r' r ) calculated by the joint probability density calculation unit 6 to a display device (not shown).

[0042] Effects of the first embodiment will be described. First, a ranging method according to the related art will be described. FIG. 13 is a diagram for explaining the principle of the ranging method according to the related art. As shown in FIG. 13, a baseline l BTwo receiver arrays S1 and S2 are positioned on a straight line. The two receiver arrays S1 and S2 are separated by a distance L. In the following explanation, the distance L will be referred to as the "baseline length". The baseline l of the target T observed by receiver array S1 B The azimuth from θ1 is used, and the baseline l of the target T observed by the receiver array S2 is used. B Let θ2 be the direction from the point. The distance r1 from the receiver array S1 to the target T can be calculated using the following equation (16).

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[0043] Figure 14 is a schematic diagram of a conventional distance measuring device 10. As shown in Figure 14, the conventional distance measuring device 10 comprises input units 11 and 12, phase adjustment processing units 21 and 22, direction calculation units 31 and 32, distance calculation unit 9, and output unit 8.

[0044] The input units 11 and 12, the phase adjustment processing units 21 and 22, and the direction calculation units 31 and 32 have the same functions as in Embodiment 1. The distance calculation unit 9 calculates the distance to the target using the target direction input from the direction calculation unit 31 and the target direction input from the direction calculation unit 32. In addition, the output unit 8 in the conventional distance measuring device 10 outputs the distance calculated by the distance calculation unit 9.

[0045] The operation of the distance measuring device 10 in the prior art will be described. The input units 11 and 12 and the phase adjustment processing units 21 and 22 operate in the same way as in Embodiment 1.

[0046] The direction calculation unit 31 processes the input phase adjustment result P1 θ The beam with the energy peak at (k,n) is detected, and the azimuth of the detected peak beam is calculated. The azimuth calculation unit 31 then calculates the target azimuth θm1(t k The distance calculation unit 9 receives the input phase adjustment processing result P2. θThe beam with the energy peak at (k,n) is detected, and the azimuth of the detected peak beam is calculated. The azimuth calculation unit 32 then calculates the target azimuth θm2(t) based on the result. k The distance calculation unit 9 receives the estimated peak bearing as the target bearing θm1(t k ) or θm²(t k It may also be used as ).

[0047] The distance calculation unit 9 calculates the input target bearing θm1(t k ) and θm²(t k Using the above equation (16) and the baseline length L, time t k Target distance rm1(t k The calculation is performed and the result is sent to the output unit 8.

[0048] Figures 15 and 16 illustrate the problems of conventional distance measurement methods. Generally, passive sonars detect target signals buried in background noise to calculate the target direction, so the observed target direction contains errors compared to the true target direction. For this reason, as shown in Figure 15, in the conventional distance measurement method using the distance measuring device 10, the distance is calculated using the target directions θm1 = θ1 + Δθ1 and θm2 = θ2 + Δθ2, which contain errors. Here, Δθ1 is the error of θ1, and Δθ2 is the error of θ2. As a result, for the true target distance r1 to the true target T, a distance rm1 = r1 + Δr1 containing errors is calculated. In this case, even though the calculated distance contains errors, the degree of the error, i.e., the certainty of the distance, is unknown.

[0049] Furthermore, if the target distance r1 is larger than the baseline length L, as shown in Figure 16, a slight error in the observed bearing can satisfy equation (17) below. In this case, the triangle formed by the observed bearing is not formed, and the probability of being unable to calculate the distance increases.

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[0050] In contrast, the distance measuring device 100 of Embodiment 1 calculates the simultaneous probability density of the target position from the probability density of the target position based on the signal received by receiver array S1 and the probability density of the target position based on the signal received by receiver array S2. The distance to the target is then acquired based on the simultaneous probability density. Thus, the distance measuring device 100 of Embodiment 1 can determine the distance without using the principle of triangulation, and can determine the distance even if the conditions of equation (17) above are met due to an error in the target direction. In other words, the distance measuring device of Embodiment 1 can determine the distance to the target regardless of the error in the observed target direction.

[0051] Figure 17 shows the probability density f when the conditions of equation (17) are met. 1r (θ' r ,r' r This is an example, and Figure 18 shows the probability density f when the conditions of equation (17) are met. 2r (θ' r ,r' r This is an example. Figure 19 shows the joint probability density f when the conditions of equation (17) are met. r (θ' r ,r' r Figure 20 is an example of the simultaneous probability density shown in Figure 19. Figures 17 and 18 show the direction (θ') where the probability density is larger compared to Figures 8 and 9, respectively. r There are slight differences in the joint probability density f shown in Figures 10 and 19. r These are different. As shown in Figure 20, even when the conditions of equation (17) are met, the distance to the target can be determined from the simultaneous probability density display in Figure 20, etc.

[0052] Furthermore, the distance measuring device 100 of Embodiment 1 can determine the degree of distance error, that is, the certainty of the distance, which could not be determined by conventional distance measuring methods, by determining the simultaneous probability density of the target's position.

[0053] The above describes embodiments of the present invention, but the present invention is not limited to the configuration of the above embodiments, and various modifications or combinations are possible within the scope of its technical idea. For example, in Embodiment 1, in order to generalize, the coordinates of the distance measurement base point are set to any (x r ,y r ) However, the coordinates (x1,0) of the receiver array S1 are used as the distance measurement base point, that is, (x r ,y r Alternatively, we can set ) = (x1, 0). This makes it possible to obtain the probability density from the position of the receiver array S1.

[0054] Note, (x r ,y r If ) = (x1,0), then instead of equations (5) to (8) above, you can use equations (18) to (21) below.

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[0055] Similarly, the coordinates (x2,0) of the receiver array S2 are used as the distance measurement base point, i.e., (x r ,y r ) = (x2, 0) is also acceptable. In this case, it becomes possible to obtain the probability density from the position of the receiver array S2. (x r ,y r If we set ) = (x², 0), then we can use equations (22) to (25) below instead of equations (5) to (8).

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[0056] Furthermore, while Embodiment 1 described a case using two receiver arrays S1 and S2, it is not limited to this, and three or more receiver arrays may be used. For example, U receiver arrays S1~S u When using the u-th receiver array S u The probability density f from the distance measurement base point when the target is observed. ur (θ' r ,r' r The following is calculated using the same principle as in Embodiment 1. Then, the receiver array S u The joint probability density f when the target is observed in (u=1~U) r (θ' r ,r' r ) can be calculated using the following formula (26).

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[0057] Furthermore, in the standard deviation calculation units 41 and 42 of Embodiment 1, the average value of the target orientations of the accumulated Q samples is calculated, and the standard deviation around the average value is calculated. However, the method for calculating the standard deviation is not limited to this method, and other methods may be used. For example, instead of the average value, αβ filtering or linear fitting may be performed on the target orientations of the accumulated Q samples to calculate the smooth orientation, and the standard deviation around the smooth orientation may be calculated.

[0058] Furthermore, in the distance measuring device 10 of Embodiment 1, the simultaneous probability density f calculated by the simultaneous probability density calculation unit 6 by the distance acquisition unit 7 is used. r (θ' r ,r' rAlthough the distance rm is acquired based on ) and output from the output unit 8, the distance measuring device 10 may be configured without a distance acquisition unit 7. In this case, the output unit 8 of the distance measuring device 10 will output the simultaneous probability density f calculated by the simultaneous probability density calculation unit 6 as distance information related to the distance to the target. r (θ' r ,r' r The output unit 8 of the distance measuring device 10 outputs either the distance rm acquired by the distance acquisition unit 7, or the simultaneous probability density f calculated by the simultaneous probability density calculation unit 6, as distance information relating to the distance from the distance measurement base point to the target. r (θ' r ,r' r It is sufficient to output at least one of the following:

[0059] The output joint probability density f r (θ' r ,r' r By displaying the information shown in Figure 12 or Figure 20 on a display device, the user viewing the display can estimate the distance rm to the target. In other words, in this case as well, the distance to the target can be determined regardless of the error in the observed target bearing. Furthermore, by outputting and displaying the simultaneous probability density, it is easy to understand how much error there is in each distance, and the certainty of the distance can also be determined.

[0060] Furthermore, in the distance acquisition unit 7 of Embodiment 1, point estimation in the field of statistics was used to determine the position with the maximum joint probability density as the target distance. However, the method of acquiring distance is not limited to this, and interval estimation may also be used to acquire the target distance. Specifically, the distance acquisition unit 7 determines the range in which the joint probability density is equal to or greater than a predetermined threshold, and assumes that the target exists within the range from the minimum distance to the maximum distance of that range, thereby acquiring the minimum target distance and the maximum target distance. The minimum target distance and the maximum target distance acquired by the distance acquisition unit 7 may then be output from the output unit 8 as the distance rm to the target.

[0061] Figure 21 illustrates the distance calculation method by the distance acquisition unit 7 in a modified example. For example, when the simultaneous probability density calculation unit 6 obtains the simultaneous probability density shown in Figure 12, the distance acquisition unit 7 finds the range R in which the simultaneous probability density is equal to or greater than a preset threshold, as shown in Figure 21. The maximum distance of the obtained range R is then set as the target maximum distance (rm_far), and the minimum distance of the range R is set as the target minimum distance (rm_near). The preset threshold may be a fixed value, or it may be a value that is a preset percentage lower than the maximum value of the simultaneous probability density. [Explanation of Symbols]

[0062] 6 Simultaneous probability density calculation unit, 7 Distance acquisition unit, 8 Output unit, 9 Distance calculation unit, 10 Distance measuring device, 11, 12 Input units, 21, 22 Phase adjustment processing unit, 31, 32 Direction calculation unit, 41, 42 Standard deviation calculation unit, 51, 52 Probability density calculation unit, 100 Distance measuring device, S1, S2 receiver array.

Claims

1. A distance measuring device that acquires distance information relating to the distance to a target based on signals from the target received by a plurality of receiver arrays, A phase-correcting processing unit that performs phase-correcting processing on the signal for each of the aforementioned receiver arrays, A direction calculation unit calculates a target direction, which is the direction in which the target is located, based on the results of the phase adjustment process for each of the aforementioned receiver arrays. A standard deviation calculation unit that calculates the standard deviation of the target direction for each of the receiver arrays, A probability density calculation unit calculates the probability density of the target's position relative to a distance measurement base point for each of the receiver arrays, based on the target direction, the standard deviation, and the probability density of the distance from the receiver array to the point where the target exists. A simultaneous probability density calculation unit calculates a simultaneous probability density by multiplying the probability densities of a plurality of the aforementioned receiver arrays, An output unit that outputs at least one of the simultaneous probability density or the distance from the distance measurement base point to the target obtained based on the simultaneous probability density as distance information, Equipped with, The probability density of the distance from the receiver array to the location where the target exists is the probability density assuming that the target exists with the same probability up to a certain distance from the receiver array. Ranging device.

2. The system includes a distance acquisition unit that acquires the distance from the distance measurement base point to the target based on the simultaneous probability density, The distance acquisition unit, The distance to the position with the highest simultaneous probability density is obtained as the distance to the target, or The distance measuring device according to claim 1, which determines a range in which the simultaneous probability density is equal to or greater than a preset threshold, and obtains the maximum distance and minimum distance within the range as the distance from the distance measuring base point to the target.

3. The distance measuring device according to claim 1 or 2, wherein the distance measuring base point is any one of the positions of the plurality of receiver arrays.

4. The distance measuring device according to claim 1 or 2, wherein the standard deviation calculation unit calculates the standard deviation using the average value of a plurality of past target directions, or a smoothed direction obtained by performing αβ filtering or linear fitting on a plurality of past target directions.

5. A distance measurement method performed by a distance measuring device that acquires distance information relating to the distance to a target based on signals from the target received by a plurality of receiver arrays, The steps include: performing phase-alignment processing on the signal for each of the aforementioned receiver arrays; A step of calculating the target direction, which is the direction in which the target is located, based on the result of the phase adjustment process for each of the aforementioned receiver arrays, A step of calculating the standard deviation of the target direction for each of the receiver arrays, A step of calculating the probability density of the target's position relative to the distance measurement base point for each receiver array, based on the target direction, the standard deviation, and the probability density of the distance from the receiver array to the point where the target exists. A step of calculating the simultaneous probability density by multiplying the probability densities of a plurality of the aforementioned receiver arrays, The steps include outputting at least one of the simultaneous probability density or the distance from the distance measurement base point to the target obtained based on the simultaneous probability density as distance information, Includes, The probability density of the distance from the receiver array to the location where the target exists is the probability density assuming that the target exists with the same probability up to a certain distance from the receiver array. Distance measurement method.

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