CN105549036B - A kind of algorithm of navigational satellite receiver Suppression of narrow band interference - Google Patents

Abstract

The invention discloses an algorithm for suppressing narrow-band interference of a navigation satellite receiver, which implements an anti-interference function in the receiver, and mainly solves the problems of low anti-narrow-band interference performance and poor real-time performance of the existing receiver, and is useful for improving satellite navigation systems in complex It is of great significance to improve its working performance in electromagnetic environment and enhance its applicability in various environments. In this method, the narrow-band interference suppression algorithm adopts correlation subtraction multi-stage Wiener filtering algorithm, which has the advantages of small calculation amount and high reliability, and can process satellite signals in real time. In the engineering implementation, FPGA is used as the core for technical implementation, and the design is carried out around the signal processing function of the ZYNQ-7000 chip and the integrated Microblaze soft core. The Microblaze soft core is used to complete the relevant subtraction and multi-stage Wiener filter algorithm to update the weights. The real-time updated weight coefficients are passed to the FIR filter for signal filtering processing to complete the anti-narrowband interference function.

Description

A Narrowband Interference Suppression Algorithm for Navigation Satellite Receiver

technical field

The invention belongs to the technical field of navigation satellite communication, and in particular relates to an algorithm for suppressing narrow-band interference of a navigation satellite receiver.

Background technique

Almighty Global Navigation Satellite System (English full name is Global Navigation Satellite System, referred to as GNSS), is a satellite positioning system established and developed relying on advanced modern science and technology. It has the characteristics of omnipotence, all-weather, continuity and real-time, and can provide Users provide precise positioning, speed measurement and timing services, and have been widely used in military and civilian fields. Therefore, countries all over the world are scrambling to develop their own satellite navigation systems, such as the GPS system of the United States, the GLONASS system of Russia, the GALILEO system of the European Union, and the Beidou navigation system of China.

However, the working environment of the satellite navigation receiver is becoming more and more complex, and the satellite signal is susceptible to intentional or unintentional interference. The anti-jamming ability of the satellite navigation receiver has become a key issue whether it can work normally. Research on satellite navigation receiver anti-jamming technology is of great significance for improving the performance of satellite navigation system in complex electromagnetic environment and enhancing its applicability in various environments.

In the satellite navigation system, narrowband interference is a very important problem, which affects the performance of the entire system. If the total power of the narrowband interference signal exceeds the interference tolerance of the system, the system performance will seriously deteriorate or even fail to work.

GNSS (Global Navigation Satellite System) is a satellite navigation and positioning system that has been continuously developed with modern technology. The receiver on the ground receives the signal from the satellite and performs calculations to realize functions such as positioning and timing. GNSS has played a huge role in fields such as military affairs, agriculture, surveying and mapping, and meteorology. At present, all countries in the world regard it as a key development area, which will have a major impact on the national economy and people's livelihood.

As early as the 1980s, with the development of the GNSS system, foreign countries have begun to conduct preliminary explorations in the field of interference suppression technology. Up to now, the research and implementation of interference has become a hot spot for scholars in the field of navigation around the world. The GNSS system adopts direct sequence spread spectrum communication technology, which can suppress the interference itself, but when the interference from the outside world is too large, it will not be able to suppress the interference, which will reduce the system performance, so this problem must be solved or improved . There are many related theories about anti-narrowband at home and abroad, but the specific practical application is still relatively scarce and cannot meet the current performance requirements.

Contents of the invention

The object of the present invention is to propose a narrow-band interference suppression algorithm for navigation satellite receivers based on correlation subtraction multi-stage Wiener filtering algorithm for the technical deficiencies in engineering practice.

Realize the technical train of thought of the present invention: take FPGA (Field Programmable GateArray, Field Programmable Gate Array) as the core to carry out technical realization, focus around the signal processing function of ZYNQ-7000 chip and integrated Microblaze soft core and design, completed Engineering Design of Correlation Subtraction Multistage Wiener Filtering Algorithm Based on Time Domain. The algorithm of the narrowband interference suppression of the navigation satellite receiver comprises the following steps:

1) After the antenna receives the navigation satellite signal, the RF module firstly performs RF front-end processing to convert the high-frequency signal into an analog intermediate-frequency signal x(t)=s(t)+j(t)+nos(t), where s( t) is the received satellite signal, j(t) is the narrow-band interference signal from the outside world, and nos(t) is the white noise of the system;

2) Send the analog intermediate frequency signal to the ADC converter for sampling, and become a digital intermediate frequency signal X(n)=S(n)+J(n)+N(n), where n represents the time series after sampling , S(n) is the sampled satellite signal, J(n) is the sampled narrowband interference signal, N(n) is the sampled noise signal;

3) Send the digital intermediate frequency signal to the FPGA for narrow-band interference suppression.

Preferred technical scheme, described step 3) in FPGA adopts adaptive FIR filter and has integrated Microblaze soft core as microprocessor as chip; Utilize integrated Microblaze soft core to carry out correlative subtraction multilevel dimension as microprocessor The nanofilter algorithm calculates the weight coefficients of the FIR filter in real time, and then sends the updated weights to the adaptive FIR filter built by the FPGA logic part to filter out the interference components in the received signal.

The preferred technical solution also includes step 4): after the FPGA filters out the interference, the signal is sent to the back end to perform satellite signal acquisition, tracking and positioning functions.

The preferred technical solution, wherein in step 1), the antenna can receive satellite signals of 4 frequency points: B3, B1, GPS and GLONASS; after the high-frequency signal is filtered and amplified by the pre-filter and the amplifier in the radio frequency module, and then passed through The RF module converts the analog IF signal.

Preferred technical scheme, wherein step 3) adopts adaptive FIR filter to filter out the interference component in the received signal, and uses Microblaze soft core to realize filtering algorithm in the chip of FPGA, wherein used correlative subtraction multistage The Wiener filtering algorithm is:

Forward iteration initialization:

d ₀ (n)= ^SH X(n) X ₀ (n)=X(n)-Sd ₀ (n)

forward iteration

for i=1,2,...,D

X _i (n)=X _i-1 (n)-h _i (n)d _i (n)

end

backward iteration initialization

e _D (n) = d _D (n)

backward iteration

for i=D, D-1,...,1

end

weight vector initialization

w _p =1

Weight Vector Iterative Calculation

for i=1,2,...,D

W _i =w _p

end

Let T _MWF ＝[S,h ₁ ,…,h _D ], W _T ＝[1,W ₁ ,…,W _D ] ^T , then W _MWF ＝T _MWF W _T

Among them, d ₀ (n) represents the expected response initial signal that needs to be approximated, H represents the conjugate transpose, d _i (n) represents the desired response signal that needs to be approximated, x(n) represents the input signal, and X(n) represents the input Signal matrix, that is, X(n)=[x(n),x(n-1),…,x(nM)] ^T , M is the filter order, X ₀ (n) represents the input observation data vector, S=[1,0,…,0] ^T is the constraint vector, D is the number of iterations, h _i is the normalized cross-correlation vector, Represents the cross-correlation vector between the input signal X(n) and the desired signal d _i (n), * represents the conjugate transpose, e _i (n) represents the estimation error of the filter output, w _i , w _p , T _MWF and W _T represents the intermediate value of the calculation process, and W _MWF represents the final calculated optimal weight vector.

In the preferred technical solution, the chip of the FPGA adopts the ZYNQ-7000 chip, and the chip is integrated with a Microblaze soft core.

Compared with the prior art, the present invention has the following advantages:

(1) Existing receiver interference suppression systems are mostly implemented in receiver antennas, mainly for broadband interference processing. The algorithms for narrowband interference suppression mostly use the LMS algorithm and the RLS algorithm for filtering. The LMS algorithm has a small amount of calculation, is simple and easy to implement in engineering, but has the disadvantage of slow convergence, cannot perform interference processing in real time, and the convergence factor is difficult to determine. Although the RLS algorithm solves the problem of convergence speed, it has the disadvantage of numerical instability, and needs to perform matrix inversion operation, which has high complexity and a large amount of calculation. The invention uses correlation subtraction multi-stage Wiener filtering algorithm, takes into account the advantages of the two algorithms, improves the convergence speed, realizes real-time performance, and is easy to implement in engineering.

(2) The present invention adopts the Microblaze soft core in the FPGA technology as the processor, which replaces the commonly used DSP and improves the integration of the chip. At the same time, the calculated weight can be transferred to the filter in the FPGA more quickly.

Description of drawings

Fig. 1 is a hardware design block diagram of the present invention;

Fig. 2 is an adaptive FIR filter structural diagram of the present invention;

Fig. 3 is the specific implementation block diagram of the narrowband interference suppression module in the present invention;

Fig. 4 is a flow chart of algorithm design of Microblaze calculation weight in the present invention.

Detailed ways

The implementation steps and effects of the present invention will be further described below with reference to the accompanying drawings:

Shown in Fig. 1 to Fig. 4 with reference to, the specific realization steps of the present invention are as follows:

Step 1, the high-frequency signals B3, B1, GPS and GLONASS of the four frequency points of the antenna receiver, that is, the frequency point of B1 is 1561.098MHz, the frequency point of B3 is 1268.52MHz, and the two frequency points of GPS L1 and L2 (L1 is 1575.42MHz , L2 is 1227.60MHz), GLONASS two frequency points L1 and L2 (L1 is 1602MHz, L2 is 1246MHz). The satellite signal is processed by the RF front-end in the RF module to obtain analog intermediate frequency signals of 62Mhz and 22.046MHz. Use the A/D converter to sample the analog intermediate frequency signal and process it into a digital intermediate frequency signal. ZYNQ-7000 processes the sampled digital intermediate frequency signal. First, it performs anti-interference processing on the digital intermediate frequency signal entering the FPGA (Field Programmable Gate Array, Field Programmable Gate Array), and then completes the capture and tracking of the signal, and finally performs the satellite signal positioning solution.

Step 2, the analog intermediate frequency signal is sent to the ADC converter for sampling, and becomes a digital intermediate frequency signal X(n)=S(n)+J(n)+N(n), where n represents the time after sampling Sequence, S(n) is the sampled satellite signal, J(n) is the sampled narrowband interference signal, N(n) is the sampled noise signal.

Step 3: buffer the digital intermediate frequency signal sampled by AD into dual-port RAM first, and Microblaze reads data from RAM as a microprocessor, implements an adaptive algorithm in Microblaze to calculate the optimal weight, and then sends the coefficients to FIR Signal processing in filters. The flag signal flag is used to control the RAM read enable signal to control the access of RAM data.

The narrowband interference suppression module uses a 50th-order adaptive FIR filter. A logic circuit is used in the FPGA to build a FIR filter whose weights are updated in real time. The weights are provided by Microblaze to process the A/D converter. The incoming digital intermediate frequency signal filters out the narrow-band interference in the signal. In the logic design, it needs to use 50 multipliers and 6-stage adders.

Use Microblaze to complete the correlation subtraction multi-stage Wiener filter algorithm to calculate the weight coefficient of the filter. The formula for calculating the adaptive weight is:

Forward iteration initialization:

d ₀ (n)= ^SH X(n) X ₀ (n)=X(n)-Sd ₀ (n)

forward iteration

for i=1,2,...,D

X _i (n)=X _i-1 (n)-h _i (n)d _i (n)

end

backward iteration initialization

e _D (n) = d _D (n)

backward iteration

for i=D,D-1,...,1

end

weight vector initialization

w _p =1

Weight Vector Iterative Calculation

for i=1,2,...,D

W _i =w _p

end

Let T _MWF ＝[S,h ₁ ,…,h _D ], W _T ＝[1,W ₁ ,…,W _D ] ^T , then W _MWF ＝T _MWF W _T

Among them, S is the normalized direction vector, S=[1,0,…,0]

Among them, d _i (n) represents the expected response signal that needs to be approximated, x(n) represents the input signal, and X(n) represents the input signal matrix, that is, X(n)=[x(n),x(n-1) ,...,x(nM)] ^T , M is the filter order, X ₀ (n) represents the input observation data vector, S=[1,0,...,0] ^T is the constraint vector, D is the number of iterations, h _i is the normalized cross-correlation vector, Represents the cross-correlation vector between the input signal X(n) and the desired signal d _i (n), * represents the conjugate transpose, e _i (n) represents the estimation error of the filter output, w _i , w _p , T _MWF and W _T represents the intermediate value of the calculation process, and W _MWF represents the final calculated optimal weight vector.

Microblaze transmits the calculated adaptive weights back to the FIR filter built by logic in the FPGA. Before the transmission, agree on the data and address commands with the FPGA to complete the communication.

Step 4: After the FPGA filters out the interference, the signal is sent to the backend for satellite signal acquisition, tracking and positioning.

The present invention realizes the anti-jamming function in the receiver, can solve the problems of low anti-narrow-band interference performance and poor real-time performance of the existing receiver, and is useful for improving the working performance of the satellite navigation system in complex electromagnetic environments and enhancing its performance in various environments. Applicability is important. In this method, the narrow-band interference suppression algorithm adopts correlation subtraction multi-stage Wiener filtering algorithm, which has the advantages of small calculation amount and high reliability, and can process satellite signals in real time. In the engineering implementation, FPGA is used as the core for technical implementation, and the design is carried out around the ZYNQ-7000 chip and the signal processing function of the integrated Microblaze soft core. Through the Microblaze soft core, the related subtraction multi-stage Wiener filter algorithm is used to update the weight value. The real-time updated weight coefficients are passed to the FIR filter for signal filtering processing to complete the anti-narrowband interference function.

Claims (5)

1. A kind of 1. method of navigational satellite receiver Suppression of narrow band interference, which is characterized in that it includes the following steps：

   1) antenna first passes around radio-frequency module progress radio-frequency front-end processing after receiving navigation satellite signal, and high-frequency signal is become mould Intend intermediate-freuqncy signal x (t)=s (t)+j (t)+no (t), wherein, s (t) is the satellite-signal received, and j (t) is from extraneous Narrow-band interference signal, no (t) are the white noise of system；

   2) analog if signal is sent into ADC converters and sampled, become digital medium-frequency signal X (n)=S (n)+J (n)+N (n), wherein, n represents the time series after over-sampling, and S (n) is the satellite-signal after sampling, and J (n) is the narrowband after sampling Interference signal, N (n) are the noise signal after sampling；

   3) digital medium-frequency signal is sent into FPGA, carries out Suppression of narrow band interference；

   The interference component in the signal received is filtered out using auto-adaptive fir filter, and is used in the chip of FPGA Microblaze is soft to verify existing filtering algorithm, wherein used correlation subtracts each other multi-Stage Wiener Filter algorithm is：

   Forward direction iteration initialization：

   d₀(n)=S^HX(n) X₀(n)=X (n)-Sd₀(n)

   Forward direction iteration

   Backward iteration initialization

   e_D(n)=d_D(n)

   Backward iteration

   Weight vector initializes

   w_p=1

   Weight vector iterates to calculate

   Enable T_MWF=[S, h₁,…,h_D],W_T=[1, W₁,…,W_D]^T, then W_MWF=T_MWFW_T

   The updated weight coefficient calculated in Microblaze is sent to FIR filtering wherein, completes interference filter, output For：

   Wherein, d₀(n) the expected response initial signal for needing to approach, d are represented_i(n) the expected response signal for needing to approach, x are represented (n) input signal is represented, X (n) represents input signal matrix, i.e. X (n)=[x (n), x (n-1) ..., x (n-M)]^T, M is filtering Device exponent number, X₀(n) the observation data vector of expression input, S=[1,0 ..., 0]^TFor constraint vector, D is iterations, h_iTo return One cross correlation vector changed,Represent input signal X (n) and desired signal d_i(n) cross correlation vector, * Represent conjugate transposition, e_i(n) evaluated error of wave filter output, w are represented_i、w_p、T_MWFAnd W_TRepresent the centre of calculating process Value, W_MWFRepresent the optimal weight vector finally calculated.
2. 2. the method for a kind of navigational satellite receiver Suppression of narrow band interference according to claim 1, which is characterized in that described It is real-time that multi-Stage Wiener Filter algorithm as microprocessor progress correlation subtracted each other using the integrated soft cores of Microblaze in step 3) The weight coefficient of FIR filter is calculated, then the weights after updating well are sent in the FIR filter that fpga logic part is built Filter out the interference component in the signal received.
3. 3. the method for a kind of navigational satellite receiver Suppression of narrow band interference according to claim 1, which is characterized in that it is also Including step 4)：After FPGA filters out interference, signal is sent to the acquisition and tracking and positioning function of rear end progress satellite-signal.
4. 4. the method for a kind of navigational satellite receiver Suppression of narrow band interference according to claim 1, which is characterized in that wherein Antenna can receive the satellite-signal of 4 frequency points in step 1)：B3, B1, GPS and GLONASS；High-frequency signal passes through radio frequency mould In block after the filter and amplification of prefilter and amplifier, then through radio-frequency module switch to analog if signal.
5. 5. the method for a kind of navigational satellite receiver Suppression of narrow band interference according to claim 1, which is characterized in that described The chip of FPGA uses ZYNQ-7000 chips, and the integrated chip has the soft cores of Microblaze.