JPH0516754B2 - - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a target signal detection device for detecting a target signal from a noise signal whose amplitude characteristics exhibit an arbitrary distribution.

[Prior Art] In radar observation, in order to detect a target object to be captured (hereinafter referred to as target), it is necessary to suppress unnecessary reflected waves from the object (hereinafter referred to as clutter) and to suppress signals from the target object (hereinafter referred to as clutter). The problem is how to detect the target signal (hereinafter referred to as target signal).
Kuratsuta has a ground plane due to reflection from the ground surface.
There are Japanese cruciferous ivy, and sea cruciferous ivy caused by reflection from the sea surface.

Conventional target signal detection devices define an appropriate noise distribution and detect a target signal based on this noise distribution.

[Problems to be Solved by the Invention] By the way, the conventional target signal detection method has a problem in that the target signal cannot be detected when the noise distribution is other than the specified one.

The present invention has been made to solve the above-mentioned problems, and an object of the present invention is to provide a target signal detection device that detects a target signal from a noise signal exhibiting an arbitrary noise distribution.

[Means for Solving the Problem] Therefore, in the present invention, a signal obtained by subtracting the average value of the logarithmically amplified signal Y from a logarithmically amplified signal Y obtained by logarithmically amplifying the input signal X containing noise having an arbitrary distribution. Logarithmic amplification/antilogarithm amplification means for outputting an antilogarithmically amplified logarithmically amplified/antilogarithmically amplified signal Z; variance value calculation means for outputting a variance value ^{σ 2} of the antilogarithmically amplified signal Z; a nonlinear calculation means that outputs a nonlinear signal U, which compares the nonlinear signal U with a preset threshold TH, and selects a nonlinear signal U larger than the threshold TH as a target signal.
A target signal detection device is constituted by a target signal detection means outputted as an OS.

[Function] The target signal detection device having the above configuration is configured such that the logarithmically amplifying/antilogarithm amplifying means inversely amplifies the logarithmically amplified signal obtained by subtracting the average value of the logarithmically amplified signal Y from the logarithmically amplified signal Y obtained by logarithmically amplifying the input signal X. Amplified/antilogarithmically amplified signal Z
The variance value calculation means calculates the variance value σ ² of the logarithmically amplified/antilogarithmically amplified signal Z, the nonlinear calculation means outputs a nonlinear signal U obtained by raising the variance value σ ² to the k power, and the target signal detection means is the nonlinear signal U and the preset threshold
TH and outputs a nonlinear signal U larger than the threshold TH as a target signal.

[Example] Hereinafter, an example of the present invention will be described in detail with reference to the accompanying drawings.

First, the signal processing theory of the target signal detection device according to the present invention will be explained.

The target signal detection device according to the present invention detects a target signal from a noise signal whose amplitude characteristics exhibit an arbitrary distribution. Here, the amplitude intensity x has a Weibull distribution and a lognormal distribution ( A case of exhibiting a Lognormal distribution will be explained.

The amplitude intensity x follows the Weibull distribution, and its probability density function P _C (X) is P _C (X) = (c/b) (x/b) ^Ci EXP [- (X/b) _C
]...(1) (Here, b is a scale parameter and c is a shape parameter.) A logarithmically amplified signal Y (Y = a ₀ ln (b ₀ The signal V obtained by subtracting the average value of Y <Y> (V=Y
-<Y>) is anti-logarithmically amplified, the initial S/N ratio is maintained. Amplification characteristics of the antilogarithmic amplifier circuit Z=C ₀ EXP (D ₀ V) ...(2) Here, C ₀ and d ₀ are constants that determine the gain of the antilogarithmic amplifier circuit, and a ₀ · d ₀ = 1 ... (3) Given the following relationship, the average value <Z> and root mean square value <Z ² > of the output Z of the antilogarithmic amplifier circuit are respectively, <Z>=∫ ^∞ ₀ Z・P _C (X)dX = C ₀ EXP (γ/C) Γ (1/C+1) ...(4) <Z ² >=∫ ^∞ ₀ Z ² P _C (X) dX = C ^{2 0} EXP (2γ/C) Γ (2/C+1) ...(5) becomes. Therefore, the variance value σ ² is σ ² =〈Z ² 〉−〈Z〉 ² =C ^{2 0} EXP(2γ/C)(Γ(2/C+1) −Γ ² (1/C+1)). The target signal OS is detected by raising this variance value σ ² to the k power.

Next, FIG. 1 is a block diagram of a target signal detection apparatus according to the present invention. In FIG. 1, the logarithmic amplification/anti-logarithm amplification means 10 converts a logarithmically amplified signal Y obtained by logarithmically amplifying the signal X shown in FIG. > subtracted and further inverse logarithmically amplified.
The anti-logarithmically amplified signal Z is outputted to the mean square value calculating means 20 and the mean square value calculating means 30, respectively. The logarithmic amplification/antilogarithm amplification means 10 is composed of a logarithmic amplification circuit 11, a delay circuit 12 constituted by a shift register, etc., an integration circuit 13, a division circuit 14, a subtraction circuit 15, and an antilogarithm amplification circuit 16. , outputs the aforementioned logarithmically amplified/anti-logarithmically amplified signal Z. That is, the logarithmic amplifier circuit 11 logarithmically amplifies the input signal X and outputs the logarithmically amplified signal Y, and the delay circuit 12 samples and quantizes the logarithmically amplified signal Y to obtain n corresponding to the amplitude y of the logarithmically amplified signal Y. sample values Y ₁ ,
Y ₂ , ..., _Yo are taken out, and the integrating circuit 13 calculates the integrated value _o 〓 ⁱ⁼¹ Y _{i ...} (7) of n sample values Y ₁ , Y ₂ ,... Yo 14 divides the integrated value by n to calculate the average value of the integrated value, that is, the average value of the logarithmically amplified signal Y <Y> 1/n _o 〓 ⁱ⁼¹ Y _i (8). Furthermore, the subtraction circuit 15 subtracts the average value <Y> of the logarithmically amplified signal Y from the logarithmically amplified signal Y,
The antilog amplification circuit 16 antilogarithmically amplifies the signal V obtained by subtracting the average value <Y> of the logarithmically amplified signal Y from the logarithmically amplified signal Y, and generates a logarithmically amplified/antilogarithmically amplified signal Z (Z=C ₀ EXP (D ₀ V )).

Here, the reason for using the logarithmic amplification/inverse logarithm increase means 10 will be explained. If the dynamic range of the input signal X is large, if this input signal is amplified by a normal linear amplifier, the output signal will be saturated if the amplitude value of the input signal is large. Therefore, when the amplitude value of the input signal is large, the amplitude value is compressed more than the linearly amplified amplitude value, and the output signal is first amplified with a logarithmic amplifier that does not saturate, and the average value is subtracted from the logarithmically amplified signal. A deviation signal is obtained, but since this amplitude deviation signal is a signal value whose amplitude has been compressed, by amplifying it with the antilogarithmic amplifier in the next stage, it can be compared to the case when using an ideal linear amplifier with a very large dynamic range. An equivalent amplitude deviation signal Z having linear characteristics can be obtained.

Further, the mean square value calculation means 20 is a square calculation circuit 2.
1. It is composed of a delay circuit 22, an integration circuit 23, and a division circuit 24, each of which is composed of a shift register, etc., and the output of the logarithmic amplification/antilogarithmic amplification circuit 10 shown in Equation 4 is The root mean square value <Z ² > of the anti-logarithmically amplified signal Z is calculated. That is, the squaring circuit 21 squares the amplitude z of the logarithmically amplified/antilogarithmically amplified signal Z to obtain an amplitude z ² , and the delay circuit 22 samples and quantizes the logarithmically amplified/antilogarithmically amplified signal Z to perform the logarithmically amplified/inversely amplified signal Z. n corresponding to the amplitude z ² of the logarithmically amplified signal Z
The integrating circuit 23 extracts n sample values Z ² ₁ , Z ² ₂ , ..., Z _2o (n is a natural number), and outputs n sample values Z ² ₁ , Z ² ₂ , ...,
The integrated value _o 〓 ⁱ⁼¹ Z ² _i ...(9) of Z ² _o is calculated, and the divider circuit 24 divides the integrated value by n, which is the root mean square value, that is, the root mean square value of the logarithmically amplified/logarithmically amplified signal Z. Calculate the value <Z ² >=1/n _o 〓 ⁱ⁼¹ Z _2i ...(10).

Further, the average value square value calculating means 30 is a delay circuit 3.
1. It is composed of an integrating circuit 32, a dividing circuit 33, and a square value calculation circuit 34, and calculates the square value <Z> ² of the average value of the logarithmically amplified/antilogarithmically amplified signal Z shown in the seventh equation. That is, the delay circuit 31 samples and quantizes the logarithmically amplified/antilogarithmically amplified signal Z to obtain n sample values Z ₁ , Z ₂ corresponding to the amplitude z of the logarithmically amplified/antilogarithmically amplified signal Z (n is a natural number). ,..., Z _o are taken out, and the integrating circuit 33 extracts n sample values Z ₁ , Z ₂ ,..., Z _o
The integrated value _o 〓 ⁱ⁼¹ Z _i ...(11) is calculated, and the dividing circuit 34 divides the integrated value by n to obtain the average value of the integrated value, that is, the average value of the logarithmically amplified/logarithmically amplified signal Z <Z> 1/2 〓 ⁱ⁼¹ Z _i ...(12) is calculated, and the square value calculation circuit 35 squares the average value to obtain the square value of the average value of the inverse logarithmically amplified signal Z〈Z〉 ² 〈Z〉 ² = N (1/n _o 〓 ⁱ⁼¹ Z _i ) ² ...(13) is calculated.

Next, the subtraction circuit 40 calculates the variance value σ ² =〈Z ² 〉−〈Z〉 ² =1/n _o ^{〓 i=} based on the root mean square value <Z 2 > and the square value of ^the average value <Z> ^{2 1} Z ² _i −(1/n _o 〓 ⁱ⁼¹ Z _i ) ² ...(14) is calculated.

Here, the well-known LOG/CFAR circuit and the logarithmic amplification/anti-logarithm amplification means 10 of the present invention will be compared, and their purpose, configuration, and output signal processing method will be explained.

Conventionally, the radar clutter level observed at any distance is approximately Reyleigh.
thought to follow the distribution. Note that the Rayleigh distribution is a special distribution when the shape parameter C=2 of the Weibull distribution shown in equation (1) of this specification.

A LOG/CFAR circuit is a receiving amplifier that includes signal processing developed for the purpose of detecting a target signal from a radar reception signal so that the probability of false alarm is constant when the probability distribution of clutter follows the Rayleigh distribution.

A conventional basic LOG/CFAR circuit consists of a logarithmic amplifier, an average value calculator, and a subtracter. A logarithmic amplifier is used in the first stage because the variance around the average value of the signal obtained by logarithmically amplifying the clutter according to the Rayleigh distribution is constant. The average value calculator calculates the average value in the range direction before and after the logarithmically amplified clutch sample value. The subtracter subtracts the average value from the logarithmically amplified sample value and outputs the result.

A target signal is detected by comparing the output signal of this subtracter with the <Z> ^binary value set to give a desired false alarm probability.

Furthermore, there is also a circuit in which the output signal of the subtracter of the basic LOG/CFAR circuit is taken out through an antilogarithmic amplifier. According to the configuration in which the inverse logarithmic amplifier is added, clutter is suppressed to a constant level while maintaining the initial S/N ratio. The false alarm probability can be made constant using a threshold value that utilizes the variance of the logarithmically amplified signal.

However, subsequent research has shown that when the radar transmission pulse width is reduced (that is, when the distance resolution is improved), the probability distribution of clutter does not follow the Rayleigh distribution, but becomes a different distribution such as the Weibull distribution or the lognormal distribution. Things gradually became clear.

If a clutter following a Weibull distribution is passed through a circuit in which an antilogarithmic amplifier is added to the basic LOG/CRAR circuit, the false alarm probability will increase. Therefore, this circuit is effective only when clutter follows Rayleigh distribution.

The logarithmic amplification/antilogarithmic amplification means 10 of the present invention is also a circuit having the same configuration as the above basic LOG/CFAR circuit in which an antilogarithmic amplifier is provided at the subsequent stage.

However, the purpose of using this logarithmic amplification/antilogarithmic amplifier means 10 in the present invention is to obtain an amplified signal with linear characteristics by amplifying the input signal without saturating it even when the input signal has a wide dynamic range. . In the present invention, since clutter having an arbitrary distribution such as the Weibull distribution or the lognormal distribution is input to the logarithmically amplifying/antilogarithmically amplifying means 10, the dispersion of the signal logarithmically amplified in the first stage is not constant. Therefore, even if a target signal is detected by comparing the output signal of the anti-logarithmic amplifier with a threshold value, the false alarm probability does not become constant.

Therefore, in the present invention, the dispersion value of the output signal Z of the logarithmic amplification/anti-logarithm amplification means 10 is calculated, and a signal obtained by nonlinearly amplifying the dispersion value is obtained, and the nonlinear amplified signal is compared with a threshold value. The target signal is detected by

FIG. 2 is a diagram showing the variance value σ ² obtained as described above. In FIG. 2, the signal X input to the logarithmic amplification/antilogarithmic amplification circuit 10 is a target signal
Even if the amplitude of OS and the amplitude of the noise signal NS are approximately the same value (see Figure 2 a), the variance value σ ² output from the subtraction circuit 40 is the value of the portion corresponding to the target signal OS. It is large, and the value of the part corresponding to the noise signal NS is almost constant and the fluctuation range is small (Figure 2 b)
), the variance value σ ² corresponding to the target signal OS can be easily detected.

FIG. 4 is a diagram for explaining the signal in FIG. 2b, and based on this FIG.
The signal in Figure b will be explained.

FIG. 4a, corresponding to FIG. 2a, is a diagram showing changes in the received amplified signal with respect to distance after the received signal is passed through a logarithmic amplification/antilogarithmic amplifier, and is a diagram showing changes in the received amplified signal with respect to distance, and the distance section r _a to r _b
, the amplitude of the target amplified signal OS is approximately 1/
It was assumed that the amplitudes were obtained with equal amplitude of (r _b ~ _ra ).

First, the target signal OS in Figure 2 a and the OS in Figure 4 a
I will explain the difference between Now, if we consider that the radar transmission pulse width is short and the distance resolution is high, and the target object is a ship, the reflected signals will be transmitted from multiple locations such as the ship's belly, bridge, chimney, and mast. The information will be obtained sequentially depending on the distance from the radar to the reflection location. Figure 2 a
In this way, the OS can
This figure shows an example of a plurality of reflected signals (signals similar to a sine wave whose amplitudes differ depending on the reflection intensity) that are received according to the distance to the reflection point (that is, according to the time).

The OS in Figure 4a is an example of a simplified target.
A signal example is shown in which a single reflecting plate (radio wave reflector) is provided at a distance r _a from the radar, and the received signal obtained from this reflecting plate is logarithmically amplified and anti-logarithmically amplified.

As a specific example, let's take the radar transmission pulse width as
If it is 80n sec, the distance between sections r _a to r _b in FIG. 4a will be approximately 12 m (meters), which corresponds to the distance resolution of the radar.

The NSs in Figure 2a and Figure 4a are the same noise signals, for example, noise signals that follow arbitrary distributions such as Weibull distribution or lognormal distribution, but the former corresponds to the received signal, and the latter corresponds to the logarithmically amplified/inverse logarithmically amplified signal. It shows the signal passed through.

When the target signal is as shown in Figure 2a or Figure 4a,
Considering the pulse height distribution probabilities around the average value <X> of each of the target signal and the noise signal, the pulse height distribution probability for the noise signal is generally as shown in FIG. 4b. This indicates that the probability that the peak value of the noise signal takes a value close to the average value is relatively high. That is, the value of the standard deviation σ _NS is relatively small.

Further, the wave height distribution probability for the target signal is as shown in FIG. 4c. This indicates that the peak value of the target signal has a high probability of taking a value far from the average value. That is, the value of standard deviation σ _OS is relatively large. Therefore, when comparing the dispersion value of the noise signal and the dispersion value of the target signal, there is a difference between the two, and the latter value is larger than the former value.

This will be explained below using specific numerical examples.

First, the amplitude intensity of a received signal follows a Weibull distribution, and the variance value σ ² when this received signal is logarithmically amplified and anti-logarithmically amplified is expressed by the above equation (6).

Here, as an example of Weibull distributed noise, there is sea clutter from the sea surface, and as an example of the actually measured value of this sea clutter, there is an example of C=1.8 and C ₀ =1 in equation (6). When this measured value is substituted into Equation (6), a numerical example of the noise variance value σ ² _W is given by Equation (38).

σ ² _W =0.38C ₀ ² =0.38 ...(38) Also, as an example of logarithmically amplifying and anti-logarithmically amplifying the target signal, the distance interval r _a ~ shown as OS in Figure 4a
Considering an equal amplitude signal of 1/(r _{b −ra} ) in r _b ,
When r _{b −ra} = 12 m and radar pulse width = 80 n sec, the signal dispersion value σ ² _OS is expressed by equation (39).

σ ² _OS = (r _b − r _a ) ² /12=12 (39) Therefore, the value of equation (39) is larger than the value of equation (38).

What is important here is that there is a magnitude relationship in which the dispersion value of the target signal obtained by logarithmically amplifying or anti-logarithmically amplifying the received signal is larger than the dispersion value of the noise signal.

Since the actual target is different from the reflector in this numerical example, it is normal that such a large difference cannot be obtained. However, if there is even a slight difference, as will be described later, by raising each value to the K power, this difference can be increased and the two can be distinguished.

In Figure 2b, each of the multiple received signals reflected from one target in Figure 2a (received signals equivalent to when multiple reflectors are installed at regular intervals) is logarithmically amplified and anti-logarithmically amplified. Dispersion value signals calculated from the signals are combined and shown as one target signal, and this relationship is the same even if the noise distribution characteristics are lognormal distribution or arbitrary distribution. Note that in this case, the sampling number n is set to an optimal value.

In this embodiment, in order to more easily detect the dispersion value σ ² corresponding to the target signal, the dispersion value σ ² is added to the nonlinear amplification circuit 50 (nonlinear amplification means).

This nonlinear amplifier circuit 50 outputs a nonlinear signal U U=(σ ^2k ) (15) obtained by dispersion value σ ² to the kth power (k is a real number). Note that the nonlinear amplifier circuit 5
As a specific example of 0, a square amplification circuit with k=2 is known. As shown in FIG. 2C, the nonlinear signal U output from the nonlinear amplifier circuit 50 has fluctuations in the portion corresponding to the noise signal NS suppressed compared to the variance value σ ² output from the subtraction circuit 40, and is The part corresponding to the standard signal OS is greatly amplified,
Detection of the variance value σ ² corresponding to the target signal OS, that is, setting of the threshold value becomes easier.

Furthermore, the target signal detection circuit 60 (target signal detection means) compares the nonlinear signal U output from the nonlinear amplifier circuit 50 with a preset threshold manually or automatically, and selects a nonlinear signal U larger than the threshold. Output as a target signal corresponding to OS.

The above-mentioned threshold TH is set manually or automatically, and in the case of manual setting, it is set while observing the nonlinear signal U with an A scope, a B scope, a PPI scope, or the like. In addition, if automatic, the average value <u> of the nonlinear signal U and the variance value around the average value
Based on Var, the false alarm probability that the noise signal NS is mistakenly detected as the target signal OS or the detection probability of the target signal OS is set to a predetermined value.

The average value <U> and the root mean square value <U ² > of the nonlinear signal U define the probability density function of the nonlinear signal U as P(U).
Then, 〈U〉=∫ ^∞ ₀ U・P(U)dU ……(16) 〈U ² 〉=∫ ^∞ ₀ U ²・P(U)dU ……(17) and the average of the nonlinear signal U The fractional value Var around the value <U> is Var=<U ² >−<U> ² ……(18). In addition, the false alarm probability Pfa is Pfa=∫ ^∞ _TH P(U)dU ...(19), which is the detection probability of the target signal OS when the amplitude t of the target signal OS is superimposed on the nonlinear signal U. Pa
is Pa=∫ ^∞ _TH P(U+t)d(U+t)...(20). Therefore, false alarm probability Pfa or detection probability Pa
The threshold value T is set so that the value T becomes a predetermined value.

Next, the threshold value TH calculated as described above
The specific values of are explained below. That is, the mth power of the variance value σ ² which is the output of the subtraction circuit 40 is M, the average value of M is <M>, the root mean square value of M is <M ² >, and the variance value of M is (<M ² > −〈M〉 ² ), and let the constants be K and A, then
One of the following values.

K・〈M〉 …(21) K・√ ^〈2〉 …(22) K・√ ^〈2〉 −〈〉 ² …(23)〈M〉＋K・√ ^〈2〉 −〈〉 ² … … ^{( 24 )} K. √ ^〈2〉 −〈〉 ² +A……(28)〈M〉+K・√ ^〈2〉 −〈〉 ² +A……(29) K・(〈M〉+√ ^〈2〉 −〈〉 ² )+A ...(30) Next, the amplitude intensity X has a lognormal distribution (Log-
A case in which the distribution has a normal distribution will be explained.

The number normal distribution for the received signal X is becomes. Here, m is the median value of the received signal X, and ρ is the average value to median ratio, ρ=<X>/m (32). Logarithmically amplified signal Y which is logarithmically amplified the received signal
(When the signal V (V = Y - <Y>) obtained by subtracting the average value <Y> of the logarithmically amplified signal Y from Y = a ₀ ln (b ₀ X) is anti-logarithmically amplified, the initial S/N ratio is maintained. Amplification characteristics of the anti-logarithmic amplifier circuit Z=C ₀ EXP (d ₀ V) ...(33) (Here, C ₀ and d ₀ are constants that determine the gain of the anti-logarithmic amplifier circuit) as a ₀・d ₀ = 1 ...(34) Given the relationship, the average value <Z> and the root mean square value <Z ² > of the output Z of the antilogarithmic amplifier circuit, which is the output of the antilogarithmic amplifier circuit, are respectively, <Z>= ∫ ^∞ ₀ Z・P(X;m,ρ)dX =C ₀・ρ ...(35)〈Z ² 〉=∫ ^∞ ₀ Z ² P(X;m,ρ)dX is =C ² ₀ ρ ⁴ ...(26) Therefore, the variance value σ ² is (36) ρ ² =〈Z ² 〉−〈Z〉 ² =C ² ₀ (ρ ⁴ −ρ ² ) ...(37). In an actual circuit, the received signal is logarithmically amplified and
Since the root mean square value <Z ² > and the square value of the average value <Z> ² of the logarithmically amplified and antilogarithmically amplified signal Z are the values described above, their explanation will be omitted.

The variance value σ ² when the amplitude strength of the received signal follows a log-normal distribution and the received signal is logarithmically amplified and anti-logarithmically amplified is shown by the above equation (37).

Here, an example of log-normal distributed noise is sea clutter from waves on the sea surface, and the actual measured values in this case include an example of ρ=1.7 and C ₀ =1. When these measured values are substituted into Equation (37), a numerical example of the noise variance value σ ² _L is expressed by Equation (40).

σ ² _L = 5.46C ₀ ² = 5.46 ...(40) Also, as an example of logarithmically amplifying and anti-logarithmically amplifying the target signal, in the case of the OS shown in Fig. 4 a, as a numerical example, equation (39) is used. The variance value σ ² _OS =12 calculated by is used.

Even in the case of this lognormal distribution, the variance value of the target signal in equation (39) is larger than the variance value of the noise signal in equation (40).

In this embodiment, a case has been described in which the target signal OS is detected from a noise signal exhibiting a Weibull distribution and a lognormal distribution, but the target signal OS can be detected even if the target signal OS is a noise signal exhibiting an arbitrary distribution.

[Effects of the Invention] As explained above, according to the present invention, the input signal
Even when the dynamic range is large, the amplified deviation signal Z with linear characteristics is amplified without saturating the input signal by logarithmic amplification/anti-logarithmic amplification means.
, calculate the dispersion value of the amplified deviation signal Z, and obtain a signal obtained by nonlinearly amplifying the dispersion value. Among the nonlinear amplified signals, the target signal has a large value, and the noise signal has a large value. Since the value becomes small, by setting an appropriate threshold, the target signal can be easily detected even when the amplitude of the target signal is smaller than the amplitude of the noise signal.

[Brief explanation of the drawing]

FIG. 1 is a block diagram of a target signal detection device according to the present invention, and FIG. 2 shows changes in received signals over time.
FIG. 3 is an explanatory diagram of a dispersion value and a new dispersion value obtained by raising the dispersion value to the k power. FIG. 3 is an explanatory diagram showing changes in the received signal over time. FIG. 4 is a diagram for explaining the signal of FIG. 2b. 10... Logarithmic amplification/anti-logarithmic amplification means, 11... Logarithmic amplification circuit, 12, 22, 31... Delay circuit, 13,
23, 32... Integration circuit, 14, 24, 33... Division circuit, 15... Subtraction circuit, 16... Anti-logarithm amplifier circuit,
20... Mean square value calculation means, 21... Square calculation circuit, 30... Average value square value calculation means, 34... Square calculation circuit, 40... Subtraction circuit, 50... Nonlinear amplifier circuit, 60... Target signal detection circuit.

Claims (1)

[Scope of Claims] 1. In a target signal detection device that detects a target signal from an input signal x mixed with noise exhibiting an arbitrary distribution, the input signal X is logarithmically amplified to provide a logarithmically amplified signal Y.
logarithmic amplification means for outputting the logarithmically amplified signal Y, average value calculation means for calculating the average value <Y> of the logarithmically amplified signal Y, subtraction means for calculating a difference signal obtained by subtracting the average value <Y> from the logarithmically amplified signal Y; Logarithmic amplification/antilogarithm amplification means configured by antilogarithmic amplification means that outputs a logarithmically amplified/antilogarithmically amplified signal Z obtained by antilogarithmically amplifying a difference signal, and a variance value σ ² of the logarithmically amplified/antilogarithmically amplified signal Z. A variance value calculating means for calculating, a nonlinear calculating means for outputting a nonlinear signal U obtained by multiplying the variance value σ ² to the k power (k is an arbitrary real number), and comparing the nonlinear signal U and a preset threshold TH. , and target signal detection means for outputting a nonlinear signal U larger than the threshold value TH as a target signal OS. 2. The threshold value in the target signal detection means is determined based on the average value of the value M obtained by raising the variance value σ ² to the m power obtained by the variance value calculation means and the variance value around the average value of M. The target signal detection device according to claim 1, wherein the false alarm probability or detection probability of the target signal is set to a predetermined value. 3. The threshold value is the value K·<M> obtained by multiplying the average value <M> of the value M, which is the m-th power of the variance value σ ² obtained by the variance value calculating means, by a constant K. The target signal detection device described in . 4 The threshold value is the root mean square value of the value M obtained by raising the variance value σ ² obtained by the variance value calculation means to the m power <M ² >
The target signal detection device according to claim 1, wherein the square root of √ ^<2> is multiplied by a constant K: K·√ ^<2> . 5. The threshold value is calculated by calculating the variance value (<M ² >−<M> ² ) around the average value <M> of the value M, which is the m-th power of the variance value σ ² obtained by the variance value calculation means, The target signal detection device according to claim 1, wherein the square root of the dispersion value is √ ^〈2〉 −〈〉 ² multiplied by a constant K: K·√ ^〈2〉 −〈〉 ² . 6. The threshold value is calculated by calculating the variance value (<M ² >−<M> ² ) around the average value <M> of the value M, which is the m-th power of the variance value σ ² obtained by the variance value calculation means, Furthermore, the square root of the variance value √〈 ² 〉−〈〉 ² is multiplied by a constant K,
The target signal detection device according to claim 1, wherein the average value <M> is further added to a value <M>+K·√ ^<2> −<> ² . 7. The threshold value is calculated by calculating the variance value (<M ² >−<M> ² ) around the average value <M> of the value M, which is the m-th power of the variance value σ ² obtained by the variance value calculation means, A patent claim that is the square root of the variance √ ^〈2〉 −〈〉 ² , the average value〈M〉, and then multiplied by a constant K: K・(〈M〉+√ ^〈2〉 −〈〉 ² ) The target signal detection device according to item 1. 8 The threshold value is the value obtained by multiplying the average value M of the value M obtained by multiplying the variance value σ ² obtained by the variance value calculation means by the constant K, and further adding the constant A, K・〈M〉+A. A target signal detection device according to claim 1. 9 The threshold value is the root mean square value of the value M obtained by raising the variance value σ ² obtained by the variance value calculating means to the m power <M ² >
Multiply the square root √〈 ² 〉 by the constant K, and then add the constant A
The target signal detection device according to claim 1, wherein the value obtained by adding K·√< ² >+A. 10 The threshold value is calculated by calculating the variance value (〈M ² >−〈M〉 ² ) around the average value <M> of the value M, which is the mth power of the variance value σ ² obtained by the variance value calculation means, The target according to claim 1, which is a value obtained by multiplying the square root of the dispersion value √ ^〈2〉 − ^〈 〉 ² by a constant K and further adding a constant A: K・√〈2〉−〈〉 ² +A Signal detection device. 11 The threshold value is calculated by calculating the variance value (〈M ² >−〈M〉 ² ) around the average value <M> of the value M, which is the mth power of the variance value σ ² obtained by the variance value calculation means, The square root of the variance √ ^〈2〉 −〈〉 ² is multiplied by the constant K, the average value〈M〉 is added, and the constant A is further added to the value 〈M〉+K・√ ^〈2〉 −〈〉 ² +A. A target signal detection device according to claim 1. 12 The threshold value is calculated by calculating the variance value (〈M ² >−〈M〉 ² ) around the average value <M> of the value M, which is the mth power of the variance value σ ² obtained by the variance value calculation means, The square root of the variance √ ^〈2〉 −〈〉 ² , the average value〈M〉 is added, the sum of the square root of the variance value and the average value is multiplied by a constant K, and the value obtained by adding the constant A is K・( The target signal detection device according to claim 1, wherein <M>+√ ^<2> −<> ² )+A.