CN103278806B - Method for removing target detection Doppler dispersion of broadband signals based on sub-band processing - Google Patents

Abstract

The invention relates to a method for eliminating Doppler dispersion of broadband signal target detection based on sub-band processing, and belongs to the technical field of radar target detection. The method of the invention decomposes the direct wave into a plurality of sub-bands, carries out coherent accumulation in each sub-band, and then performs complex superposition on the coherent accumulation results of each sub-band to obtain the final CAF output result. In order to make the accumulated target peak value of each sub-band in the same Doppler unit, it is necessary to select different accumulation time according to the carrier frequency of each sub-band. Compared with the traditional Keystone transformation method, the sub-band method does not assume the signal waveform is unchanged, which avoids the loss of signal-to-noise ratio caused by it. The invention obviously eliminates the Doppler dispersion of the target through the sub-band method, effectively improves the gain of coherent accumulation, and further improves the detection performance of the system, and is especially suitable for the application occasions where long-time accumulation is used to detect high-speed targets.

Description

Doppler Dispersion Cancellation Method for Wideband Signal Target Detection Based on Subband Processing

technical field

The invention relates to a method for eliminating Doppler dispersion of broadband signal target detection based on sub-band processing, and belongs to the technical field of radar target detection.

Background technique

The external radiation source radar uses the emission signals of various non-cooperative radiation sources existing in space to detect targets, and is a special dual multistatic radar. Because of its low cost and good electromagnetic compatibility, it has been widely valued. Commonly used non-cooperative radiation signals include FM radio signals, analog TV signals, digital TV signals, etc. Among them, the digital TV signal is an ideal irradiation source for the external radiation source radar. First of all, digital TV signals are replacing analog TV signals; secondly, digital TV uses digital modulation technology, and the transmission power is stable; moreover, the pseudo-random characteristics of digital modulation make the ambiguity function of the signal have lower side lobes; at the same time, the bandwidth of digital TV signals Wider (7.56MHz), the external radiation source radar has a relatively high range resolution, which is beneficial to the detection of low-flying targets.

However, when the digital TV external radiation source radar detects high-speed moving targets, due to the relatively wide bandwidth of the digital TV signal, there will be obvious Doppler dispersion effect, which will reduce the coherent accumulation gain, and then affect the system operating range. The longer the accumulation time is, the Doppler The effect of dispersion is more serious. The currently commonly used Keystone transformation method assumes that the signal waveform remains unchanged, and is suitable for pulse radar range migration compensation. For randomly changing digital TV signal waveforms, applying the Keystone method to eliminate chromatic dispersion will result in loss of signal-to-noise ratio.

When digital TV signals are used for target detection, the reasons for the Doppler dispersion effect are:

The radar relative bandwidth η is defined as the ratio of the signal bandwidth B to the carrier center frequency f _c , when η≥0.01, it is a wideband radar. For example, digital TV signal carrier frequency f _c =674MHz, bandwidth B=7.56MHz, relative bandwidth is

$\mathrm{<span\; class="notranslate">\; \&eta;</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; B</span>}}{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 7.56</span>}\mathrm{<span\; class="notranslate">\; MHz</span>}}{\mathrm{<span\; class="notranslate">\; 674</span>}\mathrm{<span\; class="notranslate">\; MHz</span>}}<span\; class="notranslate">\; ></span>\mathrm{<span\; class="notranslate">\; 0.01</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

Let v _r be the radial motion velocity of the target, c be the speed of light, and the carrier wavelength corresponding to the carrier frequency f _c is λ=c/f _c , then the Doppler frequency of the target echo signal is

${\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; v</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}}{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; v</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}}}{\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

When the bandwidth B of the signal is large and the target radial velocity v _r is high, the Doppler frequency f _d corresponding to different frequency components has a large difference. This phenomenon is called Doppler dispersion. In order to better illustrate the problem, give an example: Assuming the accumulation time T _int =0.8s, the frequency resolution is

$\mathrm{<span\; class="notranslate">\; \&Delta;\; f</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; int</span>}}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1.25</span>}\mathrm{<span\; class="notranslate">\; Hz</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

Table 1 lists the number of cells of Doppler spread due to Doppler dispersion corresponding to different target radial velocities.

Table 1 Relationship between target radial velocity and severity of Doppler dispersion

Due to the Doppler dispersion effect, the target energy will be dispersed in multiple Doppler units after the coherent accumulation is completed by the digital TV external radiation source radar using the cross ambiguity function (CAF), resulting in a decrease in the accumulation gain. Therefore, it is necessary to take corresponding signal processing measures to eliminate the influence of dispersion effect on target detection.

Contents of the invention

The purpose of the present invention is to effectively eliminate the Doppler dispersion in the target detection of external radiation source radar based on broadband signals, improve the coherent accumulation gain and system detection performance, and propose a wideband signal target detection Doppler based on sub-band processing Dispersion elimination method mainly adopts sub-band mutual ambiguity function (CAF) to realize Doppler dispersion elimination.

The purpose of the present invention is achieved through the following technical solutions.

A method for eliminating Doppler dispersion in broadband signal target detection based on subband processing, specifically comprising the following steps:

Step 1, subband decomposition

The broadband direct wave signal received by the antenna is decomposed into K subbands through the subband decomposition filter bank:

r _k (n)=r(n)*h _k (n) (4)

Among them, r _k (n) is the signal of the k-th sub-band obtained by sub-band decomposition of the direct wave signal vector r (n); h _k (n) is the k-th sub-band analysis filter;

The mathematical description of the subband decomposition filter bank is:

h _k (n)=h(n)e ^-j2πkn/K (5)

In the formula, k=0,1,2,...K-1, K is the number of sub-bands; h(n) is the prototype filter of the sub-band analysis filter.

Step 2, conjugate complex multiplication

The direct wave signal in each sub-band obtained in step 1 is conjugated and multiplied with the broadband echo signal received by another antenna, and the conjugate multiplication formula of the kth sub-band is:

${\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&tau;</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; e</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; \&tau;</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 6</span>}<span\; class="notranslate">\; )</span>$

Among them, e(n) is the target echo signal, and τ is the time delay.

Step 3, signal downpump

In order to reduce the amount of coherent accumulation calculations, the signals of each channel obtained after the conjugate multiplication in step 2 are sequentially subjected to anti-aliasing low-pass filtering and M-fold down-decimation. The signal obtained after downsampling of x _k (n) is:

${\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&tau;</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; l</span>}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; \&infin;</span>}{\overset{<span\; class="notranslate">\; \&infin;</span>}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}\mathrm{<span\; class="notranslate">\; g</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; l</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&tau;</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; mn</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; l</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 7</span>}<span\; class="notranslate">\; )</span>$

Among them, M is the down-decimation multiple; g(l) is an ideal low-pass filter, and its DTFT form is

Step 4, coherent accumulation time adjustment

Coherent accumulation time adjustments are performed on the sub-band signals after step 3 downsampling, so that the target peaks obtained by different sub-band k (corresponding to different wavelengths λ _k ) are in the same Doppler unit. The specific method is:

Step 4.1, obtain the points of coherent accumulation of each sub-band signal

For the target with Doppler frequency f _d , the position of the Doppler unit is:

N _{Dop_bin} =f _d /Δf=f _d T _int (9)

Wherein, the frequency resolution of target detection Δf=1/T _int , and T _int is the coherent accumulation time.

According to the Doppler frequency formula of the target echo signal Where v _r is the radial motion velocity of the target, c is the speed of light, and the carrier wavelength corresponding to the carrier frequency f _c is λ=c/f _c , and the N _{Dop_bin} where the target is located is further obtained as:

N _{Dop_bin} =2v _r f _c T _int /c (10)

In order to ensure that the Doppler unit position N _{Dop_bin} where the target is located in each subband is the same, the coherent accumulation time T _int of each subband is proportional to 1/f _c , so the number of coherent accumulation points is:

Among them, f _s is the sampling rate, f _{c_k} is the carrier frequency of the kth subband, and f _center is the center frequency of the entire digital TV signal carrier.

Step 4.2, according to the number of coherent accumulation points of each sub-band signal, intercept each sub-band signal with a length corresponding to the number of points, and use it as a sub-band signal participating in the calculation of the sub-band mutual ambiguity function.

Wherein, the starting interception position of each sub-band signal is the same.

Step five, calculate each sub-band CAF

According to the coherent accumulation time of each sub-band adjusted in step 4, the coherent accumulation result of each sub-band calculated by CAF is:

χ _k (τ,f _d )=DFT{y _k (τ,n)} (12)

Step 6, sub-band coherent accumulation synthesis

Add the complex values of the coherent accumulation results obtained for each subband to obtain the target detection result with Doppler dispersion eliminated:

${\mathrm{<span\; class="notranslate">\; \&chi;</span>}}_{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&tau;</span>}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; \&chi;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&tau;</span>}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 13</span>}<span\; class="notranslate">\; )</span>$

So far, the broadband signal target detection is completed.

Beneficial effect

The invention proposes a Doppler dispersion elimination method based on the sub-band method, which is suitable for the radar target detection of the digital TV external radiation source. The method has a simple structure, is easy to realize and has obvious effects. The sub-band method does not assume that the signal waveform is constant, which avoids the loss of signal-to-noise ratio caused by it.

Description of drawings

Fig. 1 is the Doppler dispersion elimination algorithm flowchart in the target detection based on digital television signal;

Figure 2 shows the CAF results based on Keystone transformation under different coherent accumulation time conditions, where (a) to (g) are the accumulation time of 0.4s, 0.8s, 1.2s, 1.6s, 2.0s, 2.4s, CAF results based on Keystone transformation in 2.8s;

Figure 3 shows the CAF results based on subband processing under different coherent accumulation time conditions, where (a) to (g) are the accumulation time of 0.4s, 0.8s, 1.2s, 1.6s, 2.0s, and 2.4s, respectively , CAF results based on subband processing in 2.8s;

Fig. 4 is a comparison chart of CAF signal-to-noise ratio based on subband processing and Keystone transform under different accumulation time conditions.

Detailed ways

The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

Example

This embodiment uses experimental means to verify the effectiveness of the present invention.

Experimental parameters: A digital TV broadcast tower transmits a signal with a bandwidth of 7.56MHz, a signal center frequency of 674MHz, and a baseband sampling rate of a radar signal processor of 9MHz. The test target is a civil aircraft, and the flight radial speed is about 99m/s. The accumulation time is 0.4s, 0.8s, 1.2s, 1.6s, 2.0s, 2.4s, and 2.8s, respectively, and the CAF results based on subband processing and Keystone transform are compared.

The method steps are shown in Figure 1, specifically in this embodiment:

1) The direct wave signal is decomposed into K subbands through an analysis filter bank; in this embodiment, K=32. For different broadband signals, the value of K is different. The larger K is, the better the effect of dispersion elimination is, but the calculation amount is also larger. Therefore, the value of K is selected as a trade-off between the dispersion elimination effect and the calculation amount. By convention, the subbands are raised to integer powers of 2. For digital TV signals, K is more suitable to be 32 or 64, and 32 is the most suitable.

2) Perform conjugate complex multiplication on the direct wave signal and echo signal of each sub-band;

3) In order to reduce the amount of coherent accumulation calculations, the signals of each channel after the conjugate multiplication are respectively down-decimated by 1800 times. After extraction, the data rate is 5kHz, the positive and negative frequency range is -2.5～2.5kHz, and the radial velocity coverage It is v _r =f _d λ/2=±2.5kHz×0.4451m/2=556.375m/s.

4) Coherent accumulation time adjustment, the number of coherent accumulation points is:

${\mathrm{<span\; class="notranslate">\; N</span>}}_{\mathrm{<span\; class="notranslate">\; point</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; int</span>}}{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; center</span>}}}{{\mathrm{<span\; class="notranslate">\; mf</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; k</span>}}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 9</span>}\mathrm{<span\; class="notranslate">\; MHz</span>}<span\; class="notranslate">\; \&times;</span>\mathrm{<span\; class="notranslate">\; 674</span>}\mathrm{<span\; class="notranslate">\; MHz</span>}}{\mathrm{<span\; class="notranslate">\; 1800</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; int</span>}}<span\; class="notranslate">\; /</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 3.37</span>}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; 10</span>}}^{\mathrm{<span\; class="notranslate">\; 12</span>}}<span\; class="notranslate">\; \&times;</span><span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; int</span>}}<span\; class="notranslate">\; /</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 14</span>}<span\; class="notranslate">\; )</span>$

Where T _int takes 0.4s, 0.8s, 1.2s, 1.6s, 2.0s, 2.4s, 2.8s respectively, and f _{c_k} takes the center frequency of 32 sub-bands evenly distributed between 670.22MHz and 677.78MHz.

5) Perform DFT on the data of each sub-band at different time delays τ, and calculate the CAF of 32 sub-bands.

6) The CAF results of the 32 subbands are complex-added to obtain the final CAF output result.

Figure 3 shows the CAF results of the subband method under different accumulation time conditions (the accumulation time ranges from 0.4s to 2.8s). In order to compare the effect of Doppler dispersion elimination, Fig. 2 shows the same measured data, under the same conditions, the processing result using Keystone transform.

Under different accumulation time conditions, the SNR comparison of CAF based on subband processing and Keystone transform is shown in Figure 4. It can be seen that as the accumulation time increases, the signal-to-noise ratio advantage of sub-band processing CAF begins to appear, and for this embodiment, the signal-to-noise ratio is about 1.5 dB higher. If the target speed is higher and the accumulation time is longer, the Doppler dispersion phenomenon will be more serious, so the advantages of sub-band processing CAF will be more obvious.

It can be seen from data analysis that the sub-band coherent accumulation method of the present invention can obviously eliminate the influence of Doppler dispersion and effectively improve the detection performance of the system. The invention is particularly suitable for the application occasions where long-time accumulation is used to detect high-speed targets.

The specific description above is only a specific embodiment of the present invention, and is not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, Improvements and the like should all be included within the protection scope of the present invention.

Claims (3)

1., based on the broadband signal target detection Doppler dispersion removing method of sub-band processing, it is characterized in that, specifically comprise the steps:

Step one, sub-band division

The broadband direct-path signal received by antenna, by sub-band division bank of filters, is decomposed into K subband:

r _k(n)＝r(n)*h _k(n) (4)

Wherein, r _kthe signal of a n kth subband that () obtains through sub-band division for direct-path signal vector r (n);

The mathematical description of described sub-band division bank of filters is:

h _k(n)＝h(n)e ^-j2πkn/K(5)

K=0 in formula, 1,2 ... K-1, K are number of sub-bands; h _kn () is a kth subband resolution filter; H (n) is the prototype filter of sub-band division wave filter;

Step 2, conjugate complex is taken advantage of

Direct-path signal in each subband that step one is obtained, the wideband echoes signal received with another antenna respectively does conjugate complex and takes advantage of, and a kth subband conjugate complex takes advantage of formula to be:

$x_k(\mathrm{\&tau;},n)=e(n+\mathrm{\&tau;})r_k^{*}\left(n\right)---\left(6\right)$

Wherein, e (n) is target echo signal, and τ is time delay;

Step 3, takes out under signal

The each road signal obtained after being taken advantage of by step 2 conjugate complex carries out anti-aliasing low-pass filtering, M doubly lower extraction successively; x _ktaking out rear gained signal under (τ, n) is:

$y_k(\mathrm{\&tau;},n)=\underset{l=-\&infin;}{\overset{\&infin;}{\mathrm{\&Sigma;}}}g\left(l\right)x_k(\mathrm{\&tau;},\mathrm{Mn}-l)---\left(7\right)$

Wherein M takes out multiple under being; G (l) is ideal low-pass filter, and its DTFT form is

Step 4, the correlative accumulation time adjusts

Carry out the adjustment of correlative accumulation time respectively to each way band signal after taking out under step 3, the target peak that different sub-band k is obtained is in identical doppler cells; Concrete grammar is:

Step 4.1, tries to achieve counting of the correlative accumulation of each way band signal

Doppler frequency is f _dtarget, residing doppler cells position is:

N _{Dop_bin}＝f _d/Δf＝f _dT _int(9)

Wherein, the frequency resolution Δ f=1/T of target detection _int, T _intfor the correlative accumulation time;

According to the Doppler frequency formula of target echo signal wherein v _rfor the radial motion speed of target, c is the light velocity, f _cfor carrier frequency, λ is carrier wavelength, obtains target place N further _{dop_bin}for:

N _{Dop_bin}＝2v _rf _cT _int/c (10)

The correlative accumulation time T of each subband _intbe proportional to 1/f _c, correlative accumulation count for:

Wherein f _sfor sampling rate, f _{c_k}the carrier frequency of a kth subband, f _centerit is the centre frequency of whole digital television signal carrier wave;

Step 4.2, according to counting of the correlative accumulation of each way band signal, intercepts each way band signal of corresponding length of counting, as the subband signal participating in subband cross ambiguity function and calculate;

Wherein, the initial interception position of every way band signal is identical;

Step 5, calculates each subband CAF

According to each subband correlative accumulation time that step 4 adjustment obtains, the correlative accumulation result adopting CAF to calculate each subband is:

χ _k(τ,f _d)＝DFT{y _k(τ,n)} (12)

Step 6, subband correlative accumulation is comprehensive

The correlative accumulation resulting complex values of each subband gained is added, has been eliminated the object detection results of Doppler dispersion:

${\mathrm{\&chi;}}_{\mathrm{\&Sigma;}}(\mathrm{\&tau;},f_d)=\underset{k=1}{\overset{M}{\mathrm{\&Sigma;}}}{\mathrm{\&chi;}}_k(\mathrm{\&tau;},f_d)---\left(13\right)$

So far, broadband signal target detection is completed.

2. the broadband signal target detection Doppler dispersion removing method based on sub-band processing according to claim 1, it is characterized in that: for digital television signal, K gets 32 or 64.

3. the broadband signal target detection Doppler dispersion removing method based on sub-band processing according to claim 1, is characterized in that: be suitable for adopting long time integration detection high-speed target.