JP4533820B2 - Target detection device - Google Patents

Description

  The present invention relates to a target detection apparatus that detects a target by being applied to a radar apparatus that searches or tracks a target or a reception apparatus that observes a signal waveform, and more particularly to a technique for detecting a target using wavelet transform.

  In recent years, wavelet transform is often used in the field of signal processing instead of Fourier transform and discrete cosine transform (DCT). Since the wavelet transform can efficiently process a signal whose intensity is locally distributed, it is applied in various fields such as image processing, audio signal processing, and video signal processing in a radar apparatus. The details of the wavelet transform are described in Non-Patent Document 1, for example.

  By the way, in a target detection apparatus applied to a conventional radar apparatus, in order to detect a target signal representing a target that appears only instantaneously, a large SN ratio (signal power to noise power ratio) is required. When the signal is small or the antenna gain of the radar apparatus is small, there is a problem that the SN ratio is small and the target signal cannot be detected.

  In order to solve such a problem, a radar apparatus is known that detects a target using wavelet transformation, focusing on the fact that wavelet transformation is highly sensitive to signal change points. FIG. 11 is a diagram showing a configuration of a conventional radar apparatus using such a wavelet transform. This radar apparatus includes a wavelet transform circuit 11, a development coefficient selection circuit 12, an inverse wavelet transform circuit 60, a CFAR circuit 13, and a detector 14.

In this radar apparatus, the expansion coefficients W1 to Wj generated by performing wavelet conversion on the input data in the wavelet conversion circuit 11 are sent to the expansion coefficient selection circuit 12. The expansion coefficient selection circuit 12 sends the expansion coefficient obtained by removing the expansion coefficient component that is expected to contain noise to the inverse wavelet transform circuit 60. The inverse wavelet transform circuit 60 returns the given expansion coefficient component to the frequency component again and sends it to the CFAR (Constant False Alarm Rate :) circuit 13. The CFAR circuit 13 performs CFAR processing using the reconverted data sent from the inverse wavelet transform circuit 60 and sends it to the detector 14. The detector 14 performs target detection processing based on the signal from the CFAR circuit 13 and outputs a detection signal representing the detected target. Details of the CFAR processing performed in the CFAR circuit 13 are described in Non-Patent Document 2, for example.
Nakano et al., “Signal processing and image processing using wavelets”, Kyoritsu Publishing Co., pp. 49-70, pp. 101-110 (1999) Sekine, "Radar signal processing technology", IEICE, pp. 96-106 (1991)

  However, in the conventional radar apparatus using the wavelet transform described above, the received signal is wavelet transformed, unnecessary components are removed on the wavelet axis, and then recombined to return to the signal on the time axis. Then, the signal on the time axis is compared with a predetermined threshold level to determine the presence or absence of the target. Therefore, re-synthesis processing after wavelet transform is essential, and there is a problem that the circuit configuration and the scale of signal processing increase.

  An object of the present invention is to provide a target detection apparatus that can efficiently detect a target using wavelet transform and that can reduce the circuit configuration and the scale of signal processing.

  In order to achieve the above object, the first invention provides a detection control circuit for designating a sampling position of an input signal and N (N is a positive integer) different sampling positions according to designation from the detection control circuit. An input conversion circuit that samples an input signal and outputs N signals, a wavelet conversion circuit that performs wavelet conversion on each of the N signals output from the input conversion circuit, and a target included in the input signal A detector for detecting whether each of the N wavelet expansion coefficients output from the wavelet transform circuit is greater than a predetermined threshold level at a wavelet expansion coefficient level determined according to the width of the signal to be expressed; , M of N wavelet expansion coefficients (M is a positive integer, N ≧ M) or more is a predetermined threshold. If it is detected greater than Rudoreberu, characterized in that a M / N detecting circuit for outputting a detection signal indicative of the detected targets.

  According to the first invention, since the wavelet transform detects the target using the wavelet expansion coefficient by utilizing the high sensitivity to the change point of the signal, the re-synthesis process is unnecessary, and the circuit configuration and the signal processing are performed. Can be reduced in size. Also, wavelet transform is performed on N signals whose input signal sampling positions are shifted, and if M or more of them are larger than the threshold level, a detection signal indicating that a target has been detected is output, so that it is included in the input signal. Loss due to the time position of the target signal not matching the time position of the wavelet expansion coefficient can be eliminated, and the target can be detected efficiently.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. Hereinafter, a case where the target detection device according to the present invention is applied to a radar device for searching will be described. In the following embodiments, the same or corresponding components will be described with the same reference numerals.

  FIG. 1 is a block diagram illustrating the configuration of the target detection apparatus according to the first embodiment of the present invention. The target detection apparatus includes an input conversion circuit 10, a wavelet conversion circuit 11, a development coefficient selection circuit 12, a CFAR circuit 13, a detector 14, a data storage circuit 15, an M / N detection circuit 16, and a detection control circuit 17. Yes.

  A reception signal obtained by transmitting and receiving a beam via an antenna (not shown) is input to the input conversion circuit 10 as input data f. As the input data f, data for each range cell of transmission / reception signals and data for each PRI (Pulse Repetition Interval) are used. The input conversion circuit 10 shifts the input data f in accordance with the shift control signal sent from the detection control circuit 17 and sends it to the wavelet transformation circuit 11.

The wavelet transform circuit 11 uses the signal sent from the input transform circuit 10 as input data, and performs discrete wavelet transform on this input data. Here, when the input data to the wavelet transform circuit 11 is represented by a complex signal f0 (I + jQ), the signal f to be subjected to discrete wavelet transform includes four types shown in the following equations (1) to (4). Can think.

here,
I: Real part Q: Imaginary part j: Imaginary unit The wavelet transform circuit 11 performs discrete wavelet transform using such a signal f as input data to obtain a plurality of wavelet expansion coefficients wk. The discrete wavelet transform approximates an input signal (original waveform) as shown in FIG. 3A with a scaling coefficient and a wavelet expansion coefficient. The scaling coefficient has a plurality of levels 1 to J, and the degree of approximation differs depending on each level. The wavelet expansion coefficient corresponds to the difference between the levels of the scaling coefficient.

Such a discrete wavelet transform can be represented by a time-frequency filter. FIG. 2 is a diagram illustrating filter characteristics of the discrete wavelet transform. In order of level, the frequency domain transitions from wide to low. That is, it has a filter characteristic for a short time in the high band, and has a filter characteristic for a long time as it goes to the low band. This filter characteristic can be expressed by the following equations (5) to (10), as described in Non-Patent Document 1, for example.

here,
fj: j-level approximation function (j = 1 to J)
gj: j level expansion function sk: scaling expansion coefficient (k = 1 to K)
wk: Wavelet expansion coefficient φ: Scaling function ψ: Mother wavelet function pk: Sequence determined by the mother wavelet function *: Complex conjugate Here, w shown in Equation (9) is an approximate function and an actual waveform at level j And a wavelet expansion coefficient. FIG. 3 shows how the wavelet expansion coefficient is calculated. When this wavelet expansion is used, there is an advantage that a signal representing a target can be detected with a small number of hits. The wavelet expansion coefficient obtained in the wavelet transform circuit 11 is sent to the expansion coefficient selection circuit 12.

  The expansion coefficient selection circuit 12 selects a predetermined level of expansion coefficient from the wavelet expansion coefficient sent from the wavelet transform circuit 11 according to the selection control signal sent from the detection control circuit 17, and sends it to the CFAR circuit 13. send.

  The CFAR circuit 13 generates a signal in which the false alarm probability is suppressed to a certain low level with respect to the expansion coefficient sent from the expansion coefficient selection circuit 12 and sends the signal to the detector 14. Details of the CFAR processing performed in the CFAR circuit 13 are described in Non-Patent Document 2, for example. FIG. 4 is a block diagram showing a configuration of a linear CFAR circuit that performs normalization by arithmetic mean as an example of the CFAR circuit 13. The CFAR circuit 13 includes a delay circuit 51, an adder circuit 52, an averaging processing circuit 53, and a divider circuit 54.

  The delay circuit 51 delays the input signal xi and then sends it to the adder circuit 52 and the divider circuit 54. The adder circuit 52 adds the N pieces of data sent from the delay circuit 51 during a certain period, and sends it to the averaging processing circuit 53. The averaging processing circuit 53 calculates the average value of the N pieces of data sent from the adding circuit 52 and sends it to the dividing circuit 54. The division circuit 54 divides the data sent from the delay circuit 51 by the average value and outputs the result. The CFAR circuit 13 can also be realized by a logarithmic CFAR circuit that performs normalization with a geometric mean.

  The detector 14 compares the signal sent from the CFAR circuit 13 with a predetermined threshold level. As a result of the comparison, if the signal sent from the CFAR circuit 13 is larger than the predetermined threshold level, “detected” is detected. If not, the data representing “no detection” is sent to the data storage circuit 15.

  The data storage circuit 15 sequentially stores data representing “with detection” and data representing “without detection” sent from the detector 14. The contents stored in the data storage circuit 15 are referred to by the M / N detection circuit 16.

  The M / N detection circuit 16 refers to the contents of the data storage circuit 15, and M (N is a positive integer) of N data (N is a positive integer) stored in the data storage circuit 15. When N ≧ M) is data indicating “with detection”, a detection signal indicating that the target has been detected is output.

  Next, the operation of the target detection apparatus according to Embodiment 1 of the present invention configured as described above will be described. First, the general operation will be described.

  In the wavelet transform in the wavelet transform circuit 11 described above, if an unsteady signal such as noise is included in the input signal (original waveform), the noise is included in the wavelet expansion coefficient w. Therefore, in order to remove noise from the input signal, the conventional radar apparatus shown in FIG. 11 is expected to decompose the input signal according to equations (5) to (10) and include noise in the wavelet expansion coefficient w. After the components to be removed are removed, they are re-synthesized by the equations (5) to (10) to obtain an output signal from which noise and the like are removed.

  On the other hand, in the target detection apparatus according to the present invention, focusing on the fact that the target signal to be detected is also included in the wavelet expansion coefficient w after decomposing the input signal, a predetermined signal is generated on the axis of the wavelet expansion coefficient w. The target signal is detected by comparing with the threshold level. Therefore, CFAR processing is performed on the axis of the wavelet expansion coefficient w, and a signal exceeding the threshold level is set as a detection signal.

In this case, the wavelet expansion coefficient Wc can be determined from c satisfying 2 ^c = n, where n is the width of the signal (target signal) representing the target included in the input signal. Depending on the position of the signal, the value of the wavelet expansion coefficient Wc may be small. In order to prevent this, as shown in FIGS. 5A and 5B, wavelet transformation is performed on N cases where the sampling position of the input signal is shifted and changed, and the wavelet expansion coefficient Wc is used. CFAR processing is performed, and a detection signal indicating that a target has been detected is output when M cases (N ≧ M) out of N cases exceed the threshold.

  FIG. 6 is a diagram illustrating the relationship between the time-frequency filter by wavelet transform and the target signal when the sampling position of the input signal is changed. FIG. 6 (a) shows a target signal when the input signal is sampled at the position shown in FIG. 5 (a) (position before shifting), and the target signal (the portion indicated by hatching) matches level W3. Absent. On the other hand, FIG. 6B shows a target signal when the input signal is sampled at the position shown in FIG. 5B (the position where the sampling position shown in FIG. 5A is shifted). The hatched portion) matches level W3. Thus, it can be seen that by shifting the input signal, the target signal matches the time-frequency filter and the detection efficiency can be increased.

  Next, the detailed operation of the target detection apparatus according to the first embodiment of the present invention will be described with reference to the flowchart shown in FIG.

  When the search by the radar apparatus is started, the sampling position is first shifted (step S10). That is, the detection control circuit 17 shifts the sampling position by sending a shift control signal to the input conversion circuit 10. The detection control circuit 17 sets the sampling position to the initial position for the first processing for each beam position. Thereby, the input conversion circuit 10 samples the input data at a position corresponding to the shift control signal sent from the detection control circuit 17 and sends it to the wavelet transformation circuit 11.

  Next, discrete wavelet transform (DWT) is performed (step S11). The wavelet transform circuit 11 performs discrete wavelet transform on the input data, generates wavelet expansion coefficients, and sends them to the expansion coefficient selection circuit 12. The expansion coefficient selection circuit 12 selects a wavelet expansion coefficient corresponding to the signal width of the target signal in accordance with the selection control signal from the detection control circuit 17 and sends it to the CFAR circuit 13.

  Next, CFAR processing is performed (step S12). That is, the CFAR circuit 13 performs CFAR processing on the wavelet expansion coefficient sent from the expansion coefficient selection circuit 12 and sends it to the detector 14. Next, it is checked whether or not a target signal is detected (step S13). That is, the detector 14 compares the signal sent from the CFAR circuit 13 with a predetermined threshold level. As a result of this comparison, if the signal sent from the CFAR circuit 13 is larger than a predetermined threshold level, it is determined that “detected” and “detected” data is stored (step S14). That is, when the detector 14 determines that “detection is present”, the data indicating “detection is present” is sent to the data storage circuit 15.

  On the other hand, if the signal sent from the CFAR circuit 13 is equal to or lower than the predetermined threshold level as a result of the comparison, it is judged as “no detection”, and “no detection” data is accumulated (step S15). That is, when the detector 14 determines that “no detection”, the data indicating “no detection” is sent to the data storage circuit 15.

  Next, it is checked whether or not the N sampling position shifts have been completed (step S16). If it is determined in step S16 that the process has not ended, the sequence returns to step S10, and the above-described processing is repeated. On the other hand, if it is determined that the process has been completed, then M / N detection is performed (step S17). Specifically, the M / N detection circuit 16 refers to the data stored in the data storage circuit 15 by the processing of the above steps S10 to S16, and M or more of the N data is “detected”. In the case of data that represents, a detection signal indicating that the target has been detected is output to the outside.

  Next, it is checked whether or not the search for the entire space has been completed (step S18). If it is determined in step S18 that the search for the entire space has not been completed, the sequence returns to step S10, the beam direction is changed to the next direction, and the above-described processing is repeated. On the other hand, if it is determined in step S18 that the search of the entire space has been completed, the beam direction is returned to the initial position of the search space (step S19). Thereafter, the sequence returns to step S10, and the above-described processing is repeated.

The target detection apparatus according to the second embodiment of the present invention does not use only the wavelet expansion coefficient Wc satisfying 2 ^c = n as the wavelet expansion coefficient selection method for performing the CFAR process, but before and after the wavelet expansion coefficient Wc. A plurality of (N) levels of wavelet expansion coefficients Wc + N / 2 to Wc−N / 2 + 1 are used, and as shown in FIG. 9, at least M levels out of N levels exceed a predetermined threshold level. In this case, a detection signal indicating that the target has been detected is output.

  FIG. 8 is a block diagram illustrating a configuration of the target detection apparatus according to the second embodiment of the present invention. The target detection device is configured by removing the input conversion circuit 10 from the target detection device according to the first embodiment and replacing the detection control circuit 17 of the target detection device according to the first embodiment with a detection control circuit 18. ing.

  The detection control circuit 18 generates not only one wavelet expansion coefficient Wc but also a selection control signal for sequentially selecting N levels of wavelet expansion coefficients Wc + N / 2 to Wc−N / 2 + 1 before and after that. And sent to the expansion coefficient selection circuit 12.

  Next, detailed operation of the target detection apparatus according to the second embodiment of the present invention will be described with reference to the flowchart shown in FIG.

  When the search by the radar device is started, first, the expansion coefficient is changed (step S20). That is, the detection control circuit 17 changes the level of the wavelet expansion coefficient by sending a selection control signal to the expansion coefficient selection circuit 12. Note that the detection control circuit 17 sets the level of the wavelet expansion coefficient to an initial value at the first processing for each beam position.

  Next, discrete wavelet transform (DWT) is performed (step S21). The wavelet transform circuit 11 performs discrete wavelet transform on the input data, generates wavelet expansion coefficients, and sends them to the expansion coefficient selection circuit 12. The expansion coefficient selection circuit 12 selects a wavelet expansion coefficient in accordance with the selection control signal from the detection control circuit 17 and sends it to the CFAR circuit 13.

  Next, CFAR processing is performed (step S22). That is, the CFAR circuit 13 performs CFAR processing on the wavelet expansion coefficient sent from the expansion coefficient selection circuit 12 and sends it to the detector 14. Next, it is checked whether or not a target signal is detected (step S23). That is, the detector 14 compares the signal sent from the CFAR circuit 13 with a predetermined threshold level. As a result of this comparison, if the signal sent from the CFAR circuit 13 is larger than a predetermined threshold level, it is determined that “detected”, and “detected” data is stored (step S24). That is, when the detector 14 determines that “detection is present”, the data indicating “detection is present” is sent to the data storage circuit 15. On the other hand, if the signal sent from the CFAR circuit 13 is equal to or lower than the predetermined threshold level as a result of the comparison, it is judged as “no detection”, and “no detection” data accumulation is performed (step S25). That is, when the detector 14 determines that “no detection”, the data indicating “no detection” is sent to the data storage circuit 15.

  Next, it is checked whether or not N expansion coefficient changes have been completed (step S26). If it is determined in step S26 that the process has not ended, the sequence returns to step S20, and the above-described processing is repeated. On the other hand, if it is determined that the process has been completed, then M / N detection is performed (step S27). Specifically, the M / N detection circuit 16 refers to the data stored in the data storage circuit 15 by the processing of the above steps S20 to S26, and M or more of the N data are “detected”. In the case of data that represents, a detection signal indicating that the target has been detected is output to the outside.

  Next, it is checked whether or not the search for the entire space has been completed (step S28). If it is determined in step S18 that the search of the entire space has not been completed, the sequence returns to step S20, the beam direction is changed to the next direction, and the above-described processing is repeated. On the other hand, if it is determined in step S28 that the search of the entire space has been completed, the beam direction is returned to the initial position of the search space (step S29). Thereafter, the sequence returns to step S20, and the above-described processing is repeated.

  The target detection apparatus according to the second embodiment is effective when the signal width of the target signal varies or when the signal width is not clearly known.

  It should be noted that the first embodiment and the second embodiment described above can be combined to detect the target while changing the sampling position for each of the plurality of wavelet expansion coefficients. According to this configuration, it is possible to improve target detection accuracy.

  Further, the wavelet expansion coefficient obtained by wavelet transforming the input data is configured to detect the target by performing CFAR processing. However, the present invention is not limited to CFAR processing, and a method for detecting a target using, for example, a fixed threshold level. The target may be detected by other methods.

  The target detection apparatus according to the present invention can be used for a radar apparatus or a reception apparatus.

It is a block diagram which shows the structure of the target detection apparatus which concerns on Example 1 of this invention. It is a figure which shows the filter characteristic of discrete wavelet transform. It is a figure which shows a mode that a wavelet expansion coefficient is calculated in discrete wavelet transformation. FIG. 2 is a block diagram illustrating a configuration of a CFAR circuit illustrated in FIG. 1. It is a figure for demonstrating conversion of the input signal in the target detection apparatus which concerns on Example 1 of this invention. It is a figure which shows the relationship between the time-frequency filter and target signal at the time of changing the sampling position of an input signal in the target detection apparatus which concerns on Example 1 of this invention. It is a flowchart for demonstrating the detailed operation | movement of the target detection apparatus which concerns on Example 1 of this invention. It is a block diagram which shows the structure of the target detection apparatus which concerns on Example 2 of this invention. It is a figure for demonstrating the mode of the target detection in the target detection apparatus which concerns on Example 2 of this invention. It is a flowchart for demonstrating the detailed operation | movement of the target detection apparatus which concerns on Example 2 of this invention. It is a figure for demonstrating the target detection apparatus using the conventional wavelet transform.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Input conversion circuit 11 Wavelet conversion circuit 12 Expansion coefficient selection circuit 13 CFAR circuit 14 Detector 15 Data storage circuit 16 M / N detection circuit 17, 18 Detection control circuit

Claims (1)

A detection control circuit for specifying the sampling position of the input signal;
An input conversion circuit that samples the input signal at N different sampling positions (N is a positive integer) according to designation from the detection control circuit and outputs N signals;
A wavelet transform circuit that performs wavelet transform on each of the N signals output from the input transform circuit;
Whether or not each of the N wavelet expansion coefficients output from the wavelet transform circuit is greater than a predetermined threshold level at a wavelet expansion coefficient level determined according to the width of a signal representing a target included in the input signal A detector for detecting
When the detector detects that M or more of N wavelet expansion coefficients (M is a positive integer, N ≧ M) is greater than a predetermined threshold level, the fact that a target has been detected An M / N detection circuit that outputs a detection signal of
A target detection apparatus comprising:

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