CN100334464C - Method for sonar array signal simulation by utilizing interpolation filter - Google Patents
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Abstract
The present invention discloses a method using interpolation filters to carry out sonar array signal simulation. In the method, a filter designing tool is used for generating interpolate FIR filter coefficient files and rearranging the filter coefficient files; the time delays of basis elements in arrays are divided into thick time delay control quantity and thin time delay control quantity; thick time delay processing is carried out to incident signals in a data memory according to the thick time delay control quantity; according to the thin time delay control quantity, the rearranged interpolate FIR filter coefficient files are used for carrying out filtering processing to the data after thick time delay processing for obtaining filtering processing results, namely simulated signals. The present invention combines thick time delays and thin time delays and not only can ensure sufficiently high time delay precision, but also can reach sufficiently large time delay ranges; the present invention adopts filter coefficients with rearranged order to simplify calculation for enhancing the operational speed of systems and saving hardware memory space; the method of the present invention satisfies real-time requirements and can be easily realized on DSP platforms in real time.
Description
Technical field
The present invention relates to a kind of signal simulation technology, in particular, the present invention relates to a kind of method of utilizing interpolation filter to carry out the sonar transducer array signal simulation.
Background technology
In field of underwater acoustic signal processing, the emulation of sonar transducer array signal is called anti-wave beam again and forms, and it is the directive property by in a predetermined direction, generates that each primitive receives or the signal of emission.Its general method all is by calculating the time-delay of each primitive, obtaining the primitive simulate signal corresponding with certain time-delay.
In the article " sampling rate that rises in the digital sonar is handled " of acoustic journal the 15th the 1st phase of volume of January nineteen ninety, proposed with after the zero padding of low sampling rate signal and the way of window function convolution obtain new method with high sampling rate signal, promptly insert null value between the sampled point to the low sampling rate burst, with suitable low pass filter the burst of having inserted null value is carried out filtering then and just can obtain required signal, and proved the validity of this method by simulation test.
In the article " simple and direct interpolating method is realized handling in real time " of acoustic journal the 16th the 4th phase of volume of July in 1991, proposed to realize real-time processing with a kind of interpolating method of simple and direct frequency domain zero padding.This method is when calculating the cross correlation function of two paths of signals, is not to make contrary FFT by the cross-spectrum function immediately, but earlier in the frequency domain zero padding.Because the cross-spectrum of N point real signal is in N/2 place left-right symmetric, adopt suitable real number fft algorithm, in the zero padding process, need not mobile data, thereby frequency domain zero padding reality does not need to increase operation time, then the cross-spectrum result after the zero padding is carried out contrary FFT conversion, promptly obtain the cross correlation function after the interpolation.
In sonar transducer array signal simulation technology, the requirement of precision and operand all occupies important position.And in the time-delay calculation of real-time simulation basic matrix signal, improve the important link that the signals sampling frequency is decision total system real-time and time delay precision.In above-mentioned article and many technical literatures of publishing, all related to the method for utilizing interpolation to improve sampling rate, can't carry out real-time operation but most method required times are long, or in the real-time implementation process, still existing the computing of inserting a large amount of null values, these have all influenced the speed and the real-time of system.
Consider top contradiction, generally seek the time-delay calculation that suitable interpolating method is finished the sonar transducer array signal in real time.Yet most interpolating method all exists big hardware resource, the more inaccessible problem of real-time of taking.
Summary of the invention
The objective of the invention is to overcome low precision in the existing sonar transducer array signal simulation technology or because of operand cause greatly can't real-time implementation deficiency, a kind of method of utilizing interpolation filter to carry out the sonar transducer array signal simulation is provided.
In order to realize the foregoing invention purpose, technical scheme of the present invention is:
A kind of method of utilizing interpolation filter to carry out the sonar transducer array signal simulation comprises the steps:
(1) utilize the Design of Filter instrument to generate interpolation FIR filter coefficient file Num, Num resequences to the filter coefficient file, the filter coefficient file Numl after obtaining resequencing;
(2) the time delay τ of each primitive in the calculating basic matrix
i(θ), 0≤i≤N wherein, N is the primitive number in the basic matrix, θ is the incident direction of signal;
(3) with the time delay τ of each primitive in the basic matrix
i(θ) be divided into and slightly prolong controlled quentity controlled variable Cuyan
iCarefully prolong controlled quentity controlled variable Xiyan
i, wherein slightly prolong controlled quentity controlled variable Cuyan
iCorresponding to time delay τ
iThe part in the integer that is comprised (θ) systematic sampling cycle is carefully prolonged controlled quentity controlled variable corresponding to time delay τ
iThe part in a sampling period of less than (θ);
(4) incoming signal is stored in the data-carrier store by the time sequence;
(5) according to slightly prolonging controlled quentity controlled variable Cuyan
iIncoming signal in the data storer is slightly prolonged processing, slightly prolonged and handle back data Temp
i
(6) according to carefully prolonging controlled quentity controlled variable Xiyan
i, use interpolation FIR filter coefficient file Numl to handle back data Temp to slightly prolonging
iCarry out Filtering Processing, obtain Filtering Processing result simulate signal FirOut just
i
Sorting operation to filter coefficient file Num in step (1) is: the data among the Num are begun to choose 1 point every (L-1) point from first data point, the P point is put into Numl in turn altogether, and then choose 1 point every (L-1) point since second data point, the P point is put into Numl in turn altogether; Circulating, this operates, and L data point in Num begins to finish to be selected, and last P point is put into the Numl rearmost position in turn; Replace Num as the filter coefficient file Numl; Wherein L is the interpolation ratio of wave filter.
In step (3), the described controlled quentity controlled variable Cuyan that slightly prolongs
i=K-asks whole [τ
i(θ) * Fs], the described controlled quentity controlled variable Xiyan that carefully prolongs
i=P* asks whole [abs ((τ
i(θ)-Cuyan
i* Ts)/μ)], wherein Fs is the systematic sampling frequency, and K is that the interpolation of wave filter is counted T by the treatable maximum delay amount of system, P
sBe the systematic sampling cycle, μ is the time delay precision of system, and abs asks signed magnitude arithmetic(al).
In step (5), with in the data-carrier store from Cuyan
iThe data segment of beginning slightly prolongs deal with data Temp as i primitive
i
Filtering Processing process in the step (6) is: by Xiyan
iAs start address, in Numl, find out P data point of order, as the interpolation filter coefficient of i primitive correspondence; Handle back data Temp from slightly prolonging
iFirst data point P data point beginning to take out in turn P the data point interpolation filter coefficient corresponding with i primitive do inner product of vectors respectively and calculate, with the result as vectorial FirOut
iFirst element; This operation that circulates is until from Temp
iLen data point take out P the data point interpolation filter coefficient corresponding and finish inner product calculating with i primitive, with the result as vectorial FirOut
iLen element; The Filtering Processing that promptly obtains i primitive is FirOut as a result
i, its length is Len.(Len+P)≤(Length-K), wherein, Length is the length of incoming signal, i.e. the number of data points of incoming signal in data-carrier store.
The present invention has following advantage compared to existing technology:
1) the present invention will be slightly, carefully prolong two the step time delays combine, both can guarantee sufficiently high time delay precision, can reach enough big time delay scope again.
2) the present invention adopts the THE DESIGN OF WINDOW FUNCTION interpolation FIR wave filter of Design of Filter instrument, by selecting the parameter departure, can realize high-precision broadband time delay.
3) the present invention utilizes interpolation filter carefully to prolong when handling, adopted the filter coefficient that rearranges order, thereby avoided computing that the data that will carry out interpolation filter are inserted a large amount of null values, the calculating of also having avoided null value and filter coefficient to multiply each other, make multiplication and the addition of when calculating each output sampling, only doing the individual numerical value of P (interpolation is counted), so not only improve the arithmetic speed of system, and saved hardware memory space.
4) the present invention has improved the computing velocity of basic matrix time delay algorithm, satisfies the requirement of real-time, is easy to real-time implementation on the DSP platform.
Description of drawings
Fig. 1 is the linear array synoptic diagram that the primitive among the embodiment is uniformly-spaced arranged;
Fig. 2 is the amplitude-frequency response of interpolation filter;
Fig. 3 is the distribution synoptic diagram of delay volume of the present invention;
Embodiment
Below in conjunction with the drawings and specific embodiments the present invention is described in further detail.
Real-time implementation one linear array primitive signal emulation system on DSP (ADSP 21060) platform.Systematic parameter wherein is: the linear array primitive is counted N=64, and the linear array primitive is d=1.5m at interval, signal incident angle θ=30 °, systematic sampling frequency Fs=25KHz, sampling period Ts=1/Fs=4 * 10
-5S, the treatable maximum delay amount K=1650 of system.Incoming signal is sin (2* π * f*t), and the angle theta of incoming signal and basic matrix=30 ° just obtain this warship angle on the bow of echo signal, and signal is at water medium velocity c=1500m/s.As shown in Figure 1.
Present embodiment carries out following steps:
(1) design interpolation filter:
The sample frequency of ■ system is 25kHz, i.e. sampling period T
sBe 4 * 10
-5S.As want solving simulation system time delay precision μ to reach 10
-7S, then the interpolation of interpolation filter is than L=Ts/ μ=400; By changing the interpolation ratio, can obtain different time delay precision.
■ makes the interpolation of the wave filter P=8 that counts, and according to M=L*P=400*8=3200, obtains filter order M; Then the low-pass cut-off frequencies of interpolation filter drops to fpass=Fs/2L=25kHz/400/2=31.25Hz; See Fig. 2, wherein (a) is the amplitude-frequency response of wave filter in the whole frequency band; (b) be wave filter amplitude-frequency response behind local the amplification;
■ is according to the sample frequency of wave filter, and low-pass cut-off frequencies and exponent number use the Design of Filter instrument fdatool of MATLAB to generate filter coefficient Num and Den (=1) .Num totally 3200 data points;
■ begins the data among the Num to choose 1 point every 399 from first data point, put into Numl in turn at totally 8, and then choose 1 point every 399 since second data point, put into Numl in turn at totally 8, .... this operation circulates, select up to finishing, put into the Numl rearmost position to 8 in turn since the 400 data point.Deposit Numl as a result in the filter coefficient file.
(2) the theoretical time delay value τ of each primitive in the calculating basic matrix
i(θ):
As shown in Figure 1, the nautical receiving set primitive of linear array is from left to right compiled in proper order and is H
1, H
2..., H
N, primitive be spaced apart d.For the convenience on calculating, the reference point of time is selected in H
1On.I primitive H so
1Received signal lag is in H
1, it is by path difference H
1P
iCause that i the received signal of primitive is: s
i(t))=sin{2 π f[t+ τ
i(θ)] }, i=1～N, the theoretical time delay value τ of linear array
i(θ)=(i-1) dcos θ/c.Can calculate the notional phase of each primitive according to this theory time delay, the result of calculation of present embodiment is as shown in table 1.
(3) according to time delay value τ
iThat (θ) calculates each primitive slightly prolongs controlled quentity controlled variable Cuyan
iCarefully prolong controlled quentity controlled variable Xiyan
i: as shown in Figure 3,, also satisfy the requirement of real-time, adopt a time delay of dividing thick, thin two steps to realize the multichannel primitive in order to improve computing velocity in order to take into account time delay precision and time delay scope simultaneously.With the signals sampling cycle as timing unit, integral multiple is finished dealing with by slightly prolonging in the time delay of signal sampling period, and the time delay in a sampling period of remaining less than is finished dealing with by carefully prolonging.Wherein,
Cuyan
i=K-asks whole [τ
i(θ) * Fs], Xiyan
i=P* asks whole [abs ((τ
i(θ)-Cuyan
i* * μ Ts))], " ask whole [τ
i(θ) * Fs] " be illustrated in time delay τ
iThe number of data points that comprises (θ), i.e. time delay τ
iA maximum integer sampling period that is comprised (θ), after the treatable maximum delay amount K of institute of system adjusts, Cuyan
iRepresent counting of delay data that the data of i primitive are slightly delayed time; Xiyan
iThe reference position of expression filter coefficient.
(4) incoming signal is stored in the data-carrier store (Buffer):
Incoming signal is sin (2* π * f*t), t=(0:5000-1)/Fs wherein, and f is the frequency of signal, the time span Length=5000 of signal promptly has 5000 data points among the Buffer, by the time series arrangement.
(5) slightly prolong processing:
For i primitive,, find with it at Buffer and slightly to prolong controlled quentity controlled variable Cuyan according to the mode of memory addressing
iCorresponding data point, and will be from the Buffer that this data point begins the order data segment that come the back slightly prolong deal with data Temp as i primitive
i, promptly finish and slightly prolong processing.All primitives are carried out this operation.
(6) carefully prolong processing:
A) for i primitive, by Xiyan
iAs start address, in Numl, find out the individual data point of P (=8) of order, as the interpolation filter coefficient of this primitive correspondence;
That b) takes out i primitive slightly prolongs deal with data Temp
i, from Temp
iFirst data point begin to take out P data point in turn and make c) in processing, then from Temp
iSecond data point begin to take out P data point again in turn and make c) in processing.This operation that circulates is up to from Temp
iLen data point take out P data point and finish processing.Wherein Len is 3000, because in the present embodiment, the incoming signal data length is 5000, the maximum delay amount is 1650, the value of Len should not surpass (5000-1650)=3350 so, when Len is 3000, on the position of the 3000th data point, take out 8 data points continuously, just can not produce the mistake of crossing the border.
C) P filter coefficient value of this primitive that obtains in a) with from Temp
iP the data point of taking out done inner product respectively and calculated, and the result who obtains puts into FirOut
iIn, FirOut
iPromptly be i primitive through meticulous data after prolonging processing, the simulate signal of last output just, its length is Len.
Like this, the emulation of 64 roadbeds unit signals of having used a slice dsp chip (ADSP21060) real-time implementation.In order to check effect of the present invention, will send by D/A converter by DSP according to the simulate signal that the present invention produces, use the standard phasometer to measure the actual measurement phase place of each roadbed unit signal in real time then.As shown in table 1, what notional phase was listed is the numerical value that calculates by theoretical formula, and the actual measurement phase place is the actual numerical value of measuring by phasometer.Can find out from table 1, and owing to be the primitive signal that produces in real time, so the comparison by theoretical value and measured value illustrate that this algorithm has not only satisfied the requirement of real-time, and precision is also than higher.
Table 1: time delay result relatively
| Primitive number | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
| Notional phase | 0 | -96.46 | 167.08 | 70.61 | -25.85 | -122.31 | 141.23 | 44.77 |
| The actual measurement phase place | 0 | -96.43 | 167.73 | 70.92 | -25.70 | -122.25 | 141.72 | 44.78 |
| Primitive number | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 |
| Notional phase | -51.69 | -148.16 | 115.38 | 18.92 | -77.54 | -174.00 | 89.54 | -6.93 |
| The actual measurement phase place | -51.63 | -148.35 | 115.83 | 19.16 | -77.47 | -174.19 | 89.82 | -6.89 |
| Primitive number | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 |
| Notional phase | -103.39 | 160.15 | 63.69 | -32.77 | -129.23 | 134.30 | 37.84 | -58.62 |
| The actual measurement phase place | -103.35 | 160.44 | 63.94 | -32.65 | -129.37 | 134.73 | 37.96 | -58.63 |
| Primitive number | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 |
| Notional phase | -155.08 | 108.46 | 12.00 | -84.47 | 179.07 | 82.61 | -13.85 | -110.31 |
| The actual measurement phase place | -155.39 | 108.41 | 12.26 | -84.46 | 179.51 | 82.96 | -13.79 | -110.56 |
| Primitive number | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 |
| Notional phase | 153.22 | 56.76 | -39.70 | -136.16 | 127.38 | 30.92 | -65.54 | -162.01 |
| The actual measurement phase place | 153.76 | 56.99 | -39.63 | -136.09 | 127.96 | 31.24 | -65.78 | -161.01 |
| Primitive number | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 |
| Notional phase | 101.53 | 5.07 | -91.39 | 172.15 | 75.69 | -20.78 | -117.24 | 146.30 |
| The actual measurement phase place | 101.82 | 5.14 | -91.23 | 172.66 | 76.24 | -20.65 | -117.37 | 146.64 |
| Primitive number | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 |
| Notional phase | 49.84 | -46.63 | -143.09 | 120.45 | 23.99 | -72.47 | -168.93 | 94.61 |
| The actual measurement phase place | 50.18 | -46.69 | -143.04 | 121.02 | 24.30 | -72.42 | -169.14 | 95.18 |
| Primitive number | 57 | 58 | 59 | 60 | 61 | 62 | 63 | 64 |
| Notional phase | -1.86 | -98.32 | 165.22 | 68.76 | -27.70 | -124.16 | 139.38 | 42.91 |
| The actual measurement phase place | -1.84 | -98.34 | 165.80 | 68.99 | -27.42 | -124.18 | 139.79 | 43.24 |
Claims (6)
1, a kind of method of utilizing interpolation filter to carry out the sonar transducer array signal simulation comprises the steps:
(1) utilize the Design of Filter instrument to generate interpolation FIR filter coefficient file Num, Num resequences to the filter coefficient file, the filter coefficient file Num1 after obtaining resequencing;
(2) the time delay τ of each primitive in the calculating basic matrix
i(θ), 0≤i≤N wherein, N is the primitive number in the basic matrix, θ is the incident direction of signal;
(3) with the time delay τ of each primitive in the basic matrix
i(θ) be divided into and slightly prolong controlled quentity controlled variable Cuyan
iCarefully prolong controlled quentity controlled variable Xiyan
i, wherein slightly prolong controlled quentity controlled variable Cuyan
iCorresponding to time delay τ
iThe part in the integer that is comprised (θ) systematic sampling cycle is carefully prolonged controlled quentity controlled variable corresponding to time delay τ
iThe part in a sampling period of less than (θ);
(4) incoming signal is stored in the data-carrier store by the time sequence;
(5) according to slightly prolonging controlled quentity controlled variable Cuyan
iIncoming signal in the data storer is slightly prolonged processing, slightly prolonged and handle back data Temp
i
(6) according to carefully prolonging controlled quentity controlled variable Xiyan
i, use interpolation FIR filter coefficient file Num1 to handle back data Temp to slightly prolonging
iCarry out Filtering Processing, obtain Filtering Processing result simulate signal FirOut just
i
2, the method for utilizing interpolation filter to carry out the sonar transducer array signal simulation according to claim 1, it is characterized in that, sorting operation to filter coefficient file Num in step (1) is: the data among the Num are begun to choose 1 point every (L-1) point from first data point, the P point is put into Num1 in turn altogether, and then choose 1 point every (L-1) point since second data point, the P point is put into Num1 in turn altogether; Circulating, this operates, and L data point in Num begins to finish to be selected, and last P point is put into the Num1 rearmost position in turn; Replace Num as the filter coefficient file Num1; Wherein L is the interpolation ratio of wave filter; Wherein P is that the interpolation of wave filter is counted.
3, the method for utilizing interpolation filter to carry out the sonar transducer array signal simulation according to claim 1 and 2. it is characterized in that, in step (3), the described controlled quentity controlled variable Cuyan that slightly prolongs
i=K-asks whole [τ
i(θ) * Fs], the described controlled quentity controlled variable Xiyan that carefully prolongs
i=P* asks whole [abs ((τ
i(θ)-Cuyan
i* Ts)/μ)], wherein Fs is the systematic sampling frequency, and K is that the interpolation of wave filter is counted T by the treatable maximum delay amount of system, P
sBe the systematic sampling cycle, μ is the time delay precision of system, and abs asks signed magnitude arithmetic(al).
4, the method for utilizing interpolation filter to carry out the sonar transducer array signal simulation according to claim 3 is characterized in that, in step (5), with in the data-carrier store from Cuyan
iThe data segment of beginning slightly prolongs deal with data Temp as i primitive
i
5, according to claim 1 or the 4 described methods of utilizing interpolation filter to carry out the sonar transducer array signal simulation, it is characterized in that the Filtering Processing process in the step (6) is: by Xiyan
iAs start address, in Num1, find out P data point of order, as the interpolation filter coefficient of i primitive correspondence; Handle back data Temp from slightly prolonging
iFirst data point P data point beginning to take out in turn P the data point interpolation filter coefficient corresponding with i primitive do inner product of vectors respectively and calculate, with the result as vectorial FirOut
iFirst element; This operation that circulates is until from Temp
iLen data point take out P the data point interpolation filter coefficient corresponding and finish inner product calculating with i primitive, with the result as vectorial FirOut
iLen element; The Filtering Processing that promptly obtains i primitive is FirOut as a result
i, its length is Len; Wherein P is that the interpolation of wave filter is counted.
6, the method for utilizing interpolation filter to carry out the sonar transducer array signal simulation according to claim 5, it is characterized in that, (Len+P)≤(Length-K), wherein, Length is the length of incoming signal, i.e. the number of data points of incoming signal in data-carrier store; Wherein, K is the maximum delay amount.
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| CN101190136B (en) | 2006-11-28 | 2012-07-18 | 深圳迈瑞生物医疗电子股份有限公司 | Method and device for generating real time filter coefficient |
| CN101398482B (en) * | 2008-10-24 | 2011-04-27 | 西北工业大学 | Noise field numerical computation method in passiveness wideband detection of sound reception array |
| CN101762811B (en) * | 2009-12-08 | 2012-05-30 | 中国科学院声学研究所 | Synthetic aperture sonar area target high-speed simulation method based on bin scattering |
| CN108076415B (en) * | 2016-11-16 | 2020-06-30 | 南京大学 | Real-time realization method of Doppler sound effect |
| CN108036864A (en) * | 2017-11-06 | 2018-05-15 | 武汉航空仪表有限责任公司 | A kind of FIR filtering methods of tail-rotor temperature sensor signal |
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| CN1246615A (en) * | 1998-09-02 | 2000-03-08 | 西北工业大学 | Method for processing sonar wave beams and its data processing system |
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